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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 174 new columns ({'report.per_token.throughput.value', 'report.per_token.efficiency', 'report.per_token.latency.p95', 'config.launcher.numactl', 'report.load.memory.max_process_vram', 'config.backend.hub_kwargs.local_files_only', 'config.environment.gpu_vram_mb', 'report.prefill.efficiency.value', 'report.load.memory.max_reserved', 'config.backend.device_ids', 'config.backend.intra_op_num_threads', 'config.backend.quantization_scheme', 'report.prefill.latency.values', 'config.scenario.generate_kwargs.max_new_tokens', 'config.environment.peft_commit', 'config.backend.hub_kwargs.trust_remote_code', 'config.scenario.new_tokens', 'report.prefill.latency.mean', 'config.backend.inter_op_num_threads', 'report.prefill.energy.cpu', 'config.scenario.input_shapes.num_choices', 'config.backend.task', 'config.backend.torch_dtype', 'config.backend.torch_compile', 'config.scenario.latency', 'report.decode.memory.max_ram', 'report.decode.energy.ram', 'report.per_token.memory', 'report.prefill.latency.p90', 'config.backend.hub_kwargs.revision', 'config.environment.accelerate_commit', 'report.decode.latency.total', 'config.environment.processor', 'report.prefill.energy.unit', 'report.decode.latency.p50', 'config.backend.version', 'report.load.latency.p90', 'config.backend.quantization_config.exllama_config.version', 'report.decode.latency.p99', 'config.environment.peft_version', 'config.backend.peft_type', 'report.prefill.efficiency.unit', 'report.load.latency.stdev', 'config.environment.platform', 'report.loa
...
on', 'config.backend.device', 'config.backend.quantization_config.exllama_config.max_input_len', 'report.prefill.energy.gpu', 'report.per_token.latency.total', 'config.environment.optimum_version', 'report.decode.memory.max_reserved', 'report.load.memory.max_allocated', 'report.decode.throughput.value', 'report.per_token.latency.stdev', 'report.decode.throughput.unit', 'config.backend.autocast_dtype', 'config.backend.library', 'config.environment.optimum_benchmark_version', 'report.decode.energy.cpu', 'config.backend.quantization_config.exllama_config.max_batch_size', 'report.load.throughput', 'config.environment.optimum_benchmark_commit', 'config.launcher.name', 'report.prefill.memory.max_reserved', 'config.environment.diffusers_commit', 'config.environment.optimum_commit', 'config.scenario.input_shapes.batch_size', 'report.load.energy.total', 'report.prefill.throughput.unit', 'report.per_token.latency.count', 'report.prefill.memory.max_process_vram', 'config.environment.transformers_commit', 'config.backend.low_cpu_mem_usage', 'report.prefill.memory.max_allocated', 'report.per_token.latency.p90', 'report.decode.memory.unit', 'config.environment.cpu_count', 'report.decode.latency.p90', 'config.environment.machine', 'report.decode.latency.count', 'report.per_token.latency.mean', 'report.load.memory.max_global_vram', 'config.environment.system', 'report.decode.energy.unit', 'config.backend.no_weights', 'config.scenario.memory', 'report.traceback', 'report.decode.latency.unit'}) and 34 missing columns ({'Hub ❀️', 'Architecture', 'MUSR', 'Submission Date', 'Weight type', '#Params (B)', 'BBH Raw', 'Generation', 'MoE', 'Upload To Hub Date', 'IFEval Raw', 'T', 'fullname', 'GPQA Raw', 'MMLU-PRO', 'MATH Lvl 5', 'Model', 'MMLU-PRO Raw', 'Hub License', 'GPQA', 'Available on the hub', 'IFEval', 'Not_Merged', 'Chat Template', 'Precision', 'Average ⬆️', "Maintainer's Highlight", 'Flagged', 'Model sha', 'Type', 'Base Model', 'BBH', 'MATH Lvl 5 Raw', 'MUSR Raw'}).

This happened while the csv dataset builder was generating data using

hf://datasets/optimum-benchmark/llm-perf-leaderboard/perf-df-awq-1xA10.csv (at revision 10db6ab4da6848bda3621e6fa0eb30d613c32500)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 580, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              config.name: string
              config.backend.name: string
              config.backend.version: string
              config.backend._target_: string
              config.backend.task: string
              config.backend.library: string
              config.backend.model_type: string
              config.backend.model: string
              config.backend.processor: string
              config.backend.device: string
              config.backend.device_ids: int64
              config.backend.seed: int64
              config.backend.inter_op_num_threads: double
              config.backend.intra_op_num_threads: double
              config.backend.model_kwargs.trust_remote_code: bool
              config.backend.no_weights: bool
              config.backend.device_map: double
              config.backend.torch_dtype: string
              config.backend.eval_mode: bool
              config.backend.to_bettertransformer: bool
              config.backend.low_cpu_mem_usage: double
              config.backend.attn_implementation: string
              config.backend.cache_implementation: double
              config.backend.autocast_enabled: bool
              config.backend.autocast_dtype: double
              config.backend.torch_compile: bool
              config.backend.torch_compile_target: string
              config.backend.quantization_scheme: string
              config.backend.quantization_config.bits: int64
              config.backend.quantization_config.version: string
              config.backend.quantization_config.exllama_config.version: double
              config.backend.quantization_config.exllama_config.max_input_len: double
              config.backend.quantization_config.exllama_config.max_batch_size: double
              config.backend.deepspeed_inference: bool
              config.backend.peft_type: double
              config.scenario.name: string
              config.scenario._target_: string
              config.scenario.iterations: int64
              config.scenario.duration:
              ...
              rt.decode.latency.mean: double
              report.decode.latency.stdev: double
              report.decode.latency.p50: double
              report.decode.latency.p90: double
              report.decode.latency.p95: double
              report.decode.latency.p99: double
              report.decode.latency.values: string
              report.decode.throughput.unit: string
              report.decode.throughput.value: double
              report.decode.energy.unit: string
              report.decode.energy.cpu: double
              report.decode.energy.ram: double
              report.decode.energy.gpu: double
              report.decode.energy.total: double
              report.decode.efficiency.unit: string
              report.decode.efficiency.value: double
              report.per_token.memory: double
              report.per_token.latency.unit: string
              report.per_token.latency.count: double
              report.per_token.latency.total: double
              report.per_token.latency.mean: double
              report.per_token.latency.stdev: double
              report.per_token.latency.p50: double
              report.per_token.latency.p90: double
              report.per_token.latency.p95: double
              report.per_token.latency.p99: double
              report.per_token.latency.values: string
              report.per_token.throughput.unit: string
              report.per_token.throughput.value: double
              report.per_token.energy: double
              report.per_token.efficiency: double
              report.traceback: string
              config.backend.processor_kwargs.trust_remote_code: bool
              config.backend.hub_kwargs.trust_remote_code: bool
              config.backend.hub_kwargs.revision: string
              config.backend.hub_kwargs.force_download: bool
              config.backend.hub_kwargs.local_files_only: bool
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 27877
              to
              {'T': Value(dtype='string', id=None), 'Model': Value(dtype='string', id=None), 'Average ⬆️': Value(dtype='float64', id=None), 'IFEval': Value(dtype='float64', id=None), 'IFEval Raw': Value(dtype='float64', id=None), 'BBH': Value(dtype='float64', id=None), 'BBH Raw': Value(dtype='float64', id=None), 'MATH Lvl 5': Value(dtype='float64', id=None), 'MATH Lvl 5 Raw': Value(dtype='float64', id=None), 'GPQA': Value(dtype='float64', id=None), 'GPQA Raw': Value(dtype='float64', id=None), 'MUSR': Value(dtype='float64', id=None), 'MUSR Raw': Value(dtype='float64', id=None), 'MMLU-PRO': Value(dtype='float64', id=None), 'MMLU-PRO Raw': Value(dtype='float64', id=None), 'Type': Value(dtype='string', id=None), 'Architecture': Value(dtype='string', id=None), 'Weight type': Value(dtype='string', id=None), 'Precision': Value(dtype='string', id=None), 'Not_Merged': Value(dtype='bool', id=None), 'Hub License': Value(dtype='string', id=None), '#Params (B)': Value(dtype='int64', id=None), 'Hub ❀️': Value(dtype='int64', id=None), 'Available on the hub': Value(dtype='bool', id=None), 'Model sha': Value(dtype='string', id=None), 'Flagged': Value(dtype='bool', id=None), 'MoE': Value(dtype='bool', id=None), 'Submission Date': Value(dtype='string', id=None), 'Upload To Hub Date': Value(dtype='string', id=None), 'Chat Template': Value(dtype='bool', id=None), "Maintainer's Highlight": Value(dtype='bool', id=None), 'fullname': Value(dtype='string', id=None), 'Generation': Value(dtype='int64', id=None), 'Base Model': Value(dtype='string', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1392, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1041, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 999, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1740, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 174 new columns ({'report.per_token.throughput.value', 'report.per_token.efficiency', 'report.per_token.latency.p95', 'config.launcher.numactl', 'report.load.memory.max_process_vram', 'config.backend.hub_kwargs.local_files_only', 'config.environment.gpu_vram_mb', 'report.prefill.efficiency.value', 'report.load.memory.max_reserved', 'config.backend.device_ids', 'config.backend.intra_op_num_threads', 'config.backend.quantization_scheme', 'report.prefill.latency.values', 'config.scenario.generate_kwargs.max_new_tokens', 'config.environment.peft_commit', 'config.backend.hub_kwargs.trust_remote_code', 'config.scenario.new_tokens', 'report.prefill.latency.mean', 'config.backend.inter_op_num_threads', 'report.prefill.energy.cpu', 'config.scenario.input_shapes.num_choices', 'config.backend.task', 'config.backend.torch_dtype', 'config.backend.torch_compile', 'config.scenario.latency', 'report.decode.memory.max_ram', 'report.decode.energy.ram', 'report.per_token.memory', 'report.prefill.latency.p90', 'config.backend.hub_kwargs.revision', 'config.environment.accelerate_commit', 'report.decode.latency.total', 'config.environment.processor', 'report.prefill.energy.unit', 'report.decode.latency.p50', 'config.backend.version', 'report.load.latency.p90', 'config.backend.quantization_config.exllama_config.version', 'report.decode.latency.p99', 'config.environment.peft_version', 'config.backend.peft_type', 'report.prefill.efficiency.unit', 'report.load.latency.stdev', 'config.environment.platform', 'report.loa
              ...
              on', 'config.backend.device', 'config.backend.quantization_config.exllama_config.max_input_len', 'report.prefill.energy.gpu', 'report.per_token.latency.total', 'config.environment.optimum_version', 'report.decode.memory.max_reserved', 'report.load.memory.max_allocated', 'report.decode.throughput.value', 'report.per_token.latency.stdev', 'report.decode.throughput.unit', 'config.backend.autocast_dtype', 'config.backend.library', 'config.environment.optimum_benchmark_version', 'report.decode.energy.cpu', 'config.backend.quantization_config.exllama_config.max_batch_size', 'report.load.throughput', 'config.environment.optimum_benchmark_commit', 'config.launcher.name', 'report.prefill.memory.max_reserved', 'config.environment.diffusers_commit', 'config.environment.optimum_commit', 'config.scenario.input_shapes.batch_size', 'report.load.energy.total', 'report.prefill.throughput.unit', 'report.per_token.latency.count', 'report.prefill.memory.max_process_vram', 'config.environment.transformers_commit', 'config.backend.low_cpu_mem_usage', 'report.prefill.memory.max_allocated', 'report.per_token.latency.p90', 'report.decode.memory.unit', 'config.environment.cpu_count', 'report.decode.latency.p90', 'config.environment.machine', 'report.decode.latency.count', 'report.per_token.latency.mean', 'report.load.memory.max_global_vram', 'config.environment.system', 'report.decode.energy.unit', 'config.backend.no_weights', 'config.scenario.memory', 'report.traceback', 'report.decode.latency.unit'}) and 34 missing columns ({'Hub ❀️', 'Architecture', 'MUSR', 'Submission Date', 'Weight type', '#Params (B)', 'BBH Raw', 'Generation', 'MoE', 'Upload To Hub Date', 'IFEval Raw', 'T', 'fullname', 'GPQA Raw', 'MMLU-PRO', 'MATH Lvl 5', 'Model', 'MMLU-PRO Raw', 'Hub License', 'GPQA', 'Available on the hub', 'IFEval', 'Not_Merged', 'Chat Template', 'Precision', 'Average ⬆️', "Maintainer's Highlight", 'Flagged', 'Model sha', 'Type', 'Base Model', 'BBH', 'MATH Lvl 5 Raw', 'MUSR Raw'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/optimum-benchmark/llm-perf-leaderboard/perf-df-awq-1xA10.csv (at revision 10db6ab4da6848bda3621e6fa0eb30d613c32500)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

T
string
Model
string
Average ⬆️
float64
IFEval
float64
IFEval Raw
float64
BBH
float64
BBH Raw
float64
MATH Lvl 5
float64
MATH Lvl 5 Raw
float64
GPQA
float64
GPQA Raw
float64
MUSR
float64
MUSR Raw
float64
MMLU-PRO
float64
MMLU-PRO Raw
float64
Type
string
Architecture
string
Weight type
string
Precision
string
Not_Merged
bool
Hub License
string
#Params (B)
int64
Hub ❀️
int64
Available on the hub
bool
Model sha
string
Flagged
bool
MoE
bool
Submission Date
string
Upload To Hub Date
string
Chat Template
bool
Maintainer's Highlight
bool
fullname
string
Generation
int64
Base Model
string
πŸ’¬
dfurman/CalmeRys-78B-Orpo-v0.1
50.78
81.63
0.82
61.92
0.73
37.92
0.38
20.02
0.4
36.37
0.59
66.8
0.7
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
23
true
7988deb48419c3f56bb24c139c23e5c476ec03f8
true
true
2024-09-24
2024-09-24
true
false
dfurman/CalmeRys-78B-Orpo-v0.1
1
dfurman/CalmeRys-78B-Orpo-v0.1 (Merge)
πŸ’¬
MaziyarPanahi/calme-2.4-rys-78b
50.26
80.11
0.8
62.16
0.73
37.69
0.38
20.36
0.4
34.57
0.58
66.69
0.7
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
32
true
0a35e51ffa9efa644c11816a2d56434804177acb
true
true
2024-09-03
2024-08-07
true
false
MaziyarPanahi/calme-2.4-rys-78b
2
dnhkng/RYS-XLarge
πŸ”Ά
rombodawg/Rombos-LLM-V2.5-Qwen-72b
45.39
71.55
0.72
61.27
0.72
47.58
0.48
19.8
0.4
17.32
0.46
54.83
0.59
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
other
72
17
true
5260f182e7859e13d515c4cb3926ac85ad057504
true
true
2024-09-30
2024-09-30
false
false
rombodawg/Rombos-LLM-V2.5-Qwen-72b
1
rombodawg/Rombos-LLM-V2.5-Qwen-72b (Merge)
πŸ”Ά
dnhkng/RYS-XLarge
44.75
79.96
0.8
58.77
0.71
38.97
0.39
17.9
0.38
23.72
0.5
49.2
0.54
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
70
true
0f84dd9dde60f383e1e2821496befb4ce9a11ef6
true
true
2024-08-07
2024-07-24
false
false
dnhkng/RYS-XLarge
0
dnhkng/RYS-XLarge
πŸ’¬
MaziyarPanahi/calme-2.1-rys-78b
44.14
81.36
0.81
59.47
0.71
36.4
0.36
19.24
0.39
19
0.47
49.38
0.54
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
3
true
e746f5ddc0c9b31a2382d985a4ec87fa910847c7
true
true
2024-08-08
2024-08-06
true
false
MaziyarPanahi/calme-2.1-rys-78b
1
dnhkng/RYS-XLarge
πŸ”Ά
rombodawg/Rombos-LLM-V2.5-Qwen-32b
44.1
68.27
0.68
58.26
0.7
39.12
0.39
19.57
0.4
24.73
0.5
54.62
0.59
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
32
12
true
234abe4b494dbe83ba805b791f74feb33462a33d
true
true
2024-10-07
2024-09-30
false
false
rombodawg/Rombos-LLM-V2.5-Qwen-32b
1
rombodawg/Rombos-LLM-V2.5-Qwen-32b (Merge)
πŸ’¬
MaziyarPanahi/calme-2.3-rys-78b
44.02
80.66
0.81
59.57
0.71
36.56
0.37
20.58
0.4
17
0.45
49.73
0.55
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
4
true
a8a4e55c2f7054d25c2f0ab3a3b3d806eb915180
true
true
2024-09-03
2024-08-06
true
false
MaziyarPanahi/calme-2.3-rys-78b
1
dnhkng/RYS-XLarge
πŸ’¬
MaziyarPanahi/calme-2.2-rys-78b
43.92
79.86
0.8
59.27
0.71
37.92
0.38
20.92
0.41
16.83
0.45
48.73
0.54
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
3
true
8d0dde25c9042705f65559446944a19259c3fc8e
true
true
2024-08-08
2024-08-06
true
false
MaziyarPanahi/calme-2.2-rys-78b
1
dnhkng/RYS-XLarge
πŸ’¬
MaziyarPanahi/calme-2.1-qwen2-72b
43.61
81.63
0.82
57.33
0.7
36.03
0.36
17.45
0.38
20.15
0.47
49.05
0.54
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
27
true
0369c39770f45f2464587918f2dbdb8449ea3a0d
true
true
2024-06-26
2024-06-08
true
false
MaziyarPanahi/calme-2.1-qwen2-72b
2
Qwen/Qwen2-72B
πŸ”Ά
dnhkng/RYS-XLarge-base
43.56
79.1
0.79
58.69
0.7
34.67
0.35
17.23
0.38
22.42
0.49
49.23
0.54
πŸ”Ά fine-tuned on domain-specific datasets
?
Adapter
bfloat16
true
mit
77
3
true
c718b3d9e24916e3b0347d3fdaa5e5a097c2f603
true
true
2024-08-30
2024-08-02
true
false
dnhkng/RYS-XLarge-base
0
dnhkng/RYS-XLarge-base
πŸ’¬
arcee-ai/Arcee-Nova
43.5
79.07
0.79
56.74
0.69
40.48
0.4
18.01
0.39
17.22
0.46
49.47
0.55
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
38
true
ec3bfe88b83f81481daa04b6789c1e0d32827dc5
true
true
2024-09-19
2024-07-16
true
false
arcee-ai/Arcee-Nova
0
arcee-ai/Arcee-Nova
πŸ’¬
MaziyarPanahi/calme-2.2-qwen2-72b
43.4
80.08
0.8
56.8
0.69
41.16
0.41
16.55
0.37
16.52
0.45
49.27
0.54
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
5
true
529e9bd80a76d943409bc92bb246aa7ca63dd9e6
true
true
2024-08-06
2024-07-09
true
false
MaziyarPanahi/calme-2.2-qwen2-72b
1
Qwen/Qwen2-72B
πŸ’¬
dfurman/Qwen2-72B-Orpo-v0.1
43.32
78.8
0.79
57.41
0.7
35.42
0.35
17.9
0.38
20.87
0.48
49.5
0.55
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
4
true
26c7bbaa728822c60bb47b2808972140653aae4c
true
true
2024-08-22
2024-07-05
true
false
dfurman/Qwen2-72B-Orpo-v0.1
1
dfurman/Qwen2-72B-Orpo-v0.1 (Merge)
πŸ”Ά
Undi95/MG-FinalMix-72B
43.28
80.14
0.8
57.5
0.7
33.61
0.34
18.01
0.39
21.22
0.48
49.19
0.54
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
false
other
72
3
true
6c9c2f5d052495dcd49f44bf5623d21210653c65
true
true
2024-07-13
2024-06-25
true
false
Undi95/MG-FinalMix-72B
1
Undi95/MG-FinalMix-72B (Merge)
πŸ’¬
Qwen/Qwen2-72B-Instruct
42.49
79.89
0.8
57.48
0.7
35.12
0.35
16.33
0.37
17.17
0.46
48.92
0.54
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
672
true
1af63c698f59c4235668ec9c1395468cb7cd7e79
true
true
2024-06-26
2024-05-28
false
true
Qwen/Qwen2-72B-Instruct
1
Qwen/Qwen2-72B
πŸ”Ά
abacusai/Dracarys-72B-Instruct
42.37
78.56
0.79
56.94
0.69
33.61
0.34
18.79
0.39
16.81
0.46
49.51
0.55
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
other
72
17
true
10cabc4beb57a69df51533f65e39a7ad22821370
true
true
2024-08-16
2024-08-14
true
true
abacusai/Dracarys-72B-Instruct
0
abacusai/Dracarys-72B-Instruct
πŸ”Ά
VAGOsolutions/Llama-3.1-SauerkrautLM-70b-Instruct
42.24
86.56
0.87
57.24
0.7
29.91
0.3
12.19
0.34
19.39
0.47
48.17
0.53
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
15
true
e8e74aa789243c25a3a8f7565780a402f5050bbb
true
true
2024-08-26
2024-07-29
true
false
VAGOsolutions/Llama-3.1-SauerkrautLM-70b-Instruct
0
VAGOsolutions/Llama-3.1-SauerkrautLM-70b-Instruct
πŸ’¬
anthracite-org/magnum-v1-72b
42.21
76.06
0.76
57.65
0.7
35.27
0.35
18.79
0.39
15.62
0.45
49.85
0.55
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
160
true
f8f85021bace7e8250ed8559c5b78b8b34f0c4cc
true
true
2024-09-21
2024-06-17
true
false
anthracite-org/magnum-v1-72b
2
Qwen/Qwen2-72B
πŸ’¬
alpindale/magnum-72b-v1
42.17
76.06
0.76
57.65
0.7
35.27
0.35
18.79
0.39
15.62
0.45
49.64
0.55
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
160
true
fef27e0f235ae8858b84b765db773a2a954110dd
true
true
2024-07-25
2024-06-17
true
false
alpindale/magnum-72b-v1
2
Qwen/Qwen2-72B
πŸ’¬
meta-llama/Meta-Llama-3.1-70B-Instruct
41.74
86.69
0.87
55.93
0.69
28.02
0.28
14.21
0.36
17.69
0.46
47.88
0.53
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
615
true
b9461463b511ed3c0762467538ea32cf7c9669f2
true
true
2024-08-15
2024-07-16
true
true
meta-llama/Meta-Llama-3.1-70B-Instruct
1
meta-llama/Meta-Llama-3.1-70B
πŸ”Ά
dnhkng/RYS-Llama3.1-Large
41.6
84.92
0.85
55.41
0.69
28.4
0.28
16.55
0.37
17.09
0.46
47.21
0.52
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
mit
81
1
true
52cc979de78155b33689efa48f52a8aab184bd86
true
true
2024-08-22
2024-08-11
true
false
dnhkng/RYS-Llama3.1-Large
0
dnhkng/RYS-Llama3.1-Large
πŸ”Ά
rombodawg/Rombos-LLM-V2.6-Nemotron-70b
41.49
75.27
0.75
55.81
0.69
30.59
0.31
20.81
0.41
18.39
0.47
48.1
0.53
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
1
true
951c9cdf68d6e679c78625d1a1f396eb71cdf746
true
true
2024-10-17
2024-10-17
false
false
rombodawg/Rombos-LLM-V2.6-Nemotron-70b
0
rombodawg/Rombos-LLM-V2.6-Nemotron-70b
πŸ’¬
anthracite-org/magnum-v2-72b
41.15
75.6
0.76
57.85
0.7
31.65
0.32
18.12
0.39
14.18
0.44
49.51
0.55
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
31
true
c9c5826ef42b9fcc8a8e1079be574481cf0b6cc6
true
true
2024-09-05
2024-08-18
true
false
anthracite-org/magnum-v2-72b
2
Qwen/Qwen2-72B
πŸ’¬
abacusai/Smaug-Qwen2-72B-Instruct
41.08
78.25
0.78
56.27
0.69
35.35
0.35
14.88
0.36
15.18
0.44
46.56
0.52
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
8
true
af015925946d0c60ef69f512c3b35f421cf8063d
true
true
2024-07-29
2024-06-26
true
true
abacusai/Smaug-Qwen2-72B-Instruct
0
abacusai/Smaug-Qwen2-72B-Instruct
🀝
paulml/ECE-ILAB-Q1
40.93
78.65
0.79
53.7
0.67
26.13
0.26
18.23
0.39
18.81
0.46
50.06
0.55
🀝 base merges and moerges
Qwen2ForCausalLM
Original
bfloat16
false
other
72
0
true
393bea0ee85e4c752acd5fd77ce07f577fc13bd9
true
true
2024-09-16
2024-06-06
false
false
paulml/ECE-ILAB-Q1
0
paulml/ECE-ILAB-Q1
πŸ”Ά
KSU-HW-SEC/Llama3.1-70b-SVA-FT-1000step
40.33
72.38
0.72
55.49
0.69
29.61
0.3
19.46
0.4
17.83
0.46
47.24
0.53
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
b195fea0d8f350ff29243d4e88654b1baa5af79e
true
true
2024-09-08
null
false
false
KSU-HW-SEC/Llama3.1-70b-SVA-FT-1000step
0
Removed
πŸ’¬
MaziyarPanahi/calme-2.3-llama3.1-70b
40.3
86.05
0.86
55.59
0.69
21.45
0.21
12.53
0.34
17.74
0.46
48.48
0.54
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
null
70
3
false
a39c79250721b75beefa1b1763895eafd010f6f6
true
true
2024-09-18
2024-09-10
true
false
MaziyarPanahi/calme-2.3-llama3.1-70b
2
meta-llama/Meta-Llama-3.1-70B
πŸ’¬
upstage/solar-pro-preview-instruct
39.61
84.16
0.84
54.82
0.68
20.09
0.2
16.11
0.37
15.01
0.44
47.48
0.53
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
SolarForCausalLM
Original
bfloat16
true
mit
22
407
true
b4db141b5fb08b23f8bc323bc34e2cff3e9675f8
true
true
2024-09-11
2024-09-09
true
true
upstage/solar-pro-preview-instruct
0
upstage/solar-pro-preview-instruct
πŸ”Ά
pankajmathur/orca_mini_v7_72b
39.06
59.3
0.59
55.06
0.68
26.44
0.26
18.01
0.39
24.21
0.51
51.35
0.56
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
72
11
true
447f11912cfa496e32e188a55214043a05760d3a
true
true
2024-06-26
2024-06-26
false
false
pankajmathur/orca_mini_v7_72b
0
pankajmathur/orca_mini_v7_72b
πŸ’¬
MaziyarPanahi/calme-2.1-qwen2.5-72b
38.38
86.62
0.87
61.66
0.73
2.27
0.02
15.1
0.36
13.3
0.43
51.32
0.56
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
1
true
eb6c92dec932070ea872f39469ca5b9daf2d34e6
true
true
2024-09-26
2024-09-19
true
false
MaziyarPanahi/calme-2.1-qwen2.5-72b
1
Qwen/Qwen2.5-72B
🀝
gbueno86/Meta-LLama-3-Cat-Smaug-LLama-70b
38.27
80.72
0.81
51.51
0.67
26.81
0.27
10.29
0.33
15
0.44
45.28
0.51
🀝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
llama3
70
1
true
2d73b7e1c7157df482555944d6a6b1362bc6c3c5
true
true
2024-06-27
2024-05-24
true
false
gbueno86/Meta-LLama-3-Cat-Smaug-LLama-70b
1
gbueno86/Meta-LLama-3-Cat-Smaug-LLama-70b (Merge)
πŸ’¬
Qwen/Qwen2.5-72B-Instruct
38.21
86.38
0.86
61.87
0.73
1.21
0.01
16.67
0.38
11.74
0.42
51.4
0.56
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
347
true
a13fff9ad76700c7ecff2769f75943ba8395b4a7
true
true
2024-10-16
2024-09-16
true
true
Qwen/Qwen2.5-72B-Instruct
1
Qwen/Qwen2.5-72B
πŸ’¬
MaziyarPanahi/calme-2.2-qwen2.5-72b
38.01
84.77
0.85
61.8
0.73
3.63
0.04
14.54
0.36
12.02
0.42
51.31
0.56
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
5
true
c6c7fdf70d8bf81364108975eb8ba78eecac83d4
true
true
2024-09-26
2024-09-19
true
false
MaziyarPanahi/calme-2.2-qwen2.5-72b
1
Qwen/Qwen2.5-72B
πŸ’¬
MaziyarPanahi/calme-2.2-llama3-70b
37.98
82.08
0.82
48.57
0.64
22.96
0.23
12.19
0.34
15.3
0.44
46.74
0.52
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
17
true
95366b974baedee4d95c1e841bc3d15e94753804
true
true
2024-06-26
2024-04-27
true
false
MaziyarPanahi/calme-2.2-llama3-70b
2
meta-llama/Meta-Llama-3-70B
🟒
Qwen/Qwen2.5-72B
37.94
41.37
0.41
54.62
0.68
36.1
0.36
20.69
0.41
19.64
0.48
55.2
0.6
🟒 pretrained
Qwen2ForCausalLM
Original
bfloat16
true
other
72
33
true
587cc4061cf6a7cc0d429d05c109447e5cf063af
true
true
2024-09-19
2024-09-15
false
true
Qwen/Qwen2.5-72B
0
Qwen/Qwen2.5-72B
πŸ”Ά
VAGOsolutions/Llama-3-SauerkrautLM-70b-Instruct
37.82
80.45
0.8
52.03
0.67
21.68
0.22
10.4
0.33
13.54
0.43
48.8
0.54
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
other
70
21
true
707cfd1a93875247c0223e0c7e3d86d58c432318
true
true
2024-06-26
2024-04-24
true
false
VAGOsolutions/Llama-3-SauerkrautLM-70b-Instruct
0
VAGOsolutions/Llama-3-SauerkrautLM-70b-Instruct
🌸
Qwen/Qwen2-VL-72B-Instruct
37.69
59.82
0.6
56.31
0.69
23.34
0.23
18.34
0.39
15.89
0.45
52.41
0.57
🌸 multimodal
Qwen2VLForConditionalGeneration
Original
bfloat16
true
other
73
137
true
f400120e59a6196b024298b7d09fb517f742db7d
true
true
2024-10-20
2024-09-17
true
true
Qwen/Qwen2-VL-72B-Instruct
0
Qwen/Qwen2-VL-72B-Instruct
🟒
Qwen/Qwen2.5-32B
37.54
40.77
0.41
53.95
0.68
32.85
0.33
21.59
0.41
22.7
0.5
53.39
0.58
🟒 pretrained
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
32
22
true
ff23665d01c3665be5fdb271d18a62090b65c06d
true
true
2024-09-19
2024-09-15
false
true
Qwen/Qwen2.5-32B
0
Qwen/Qwen2.5-32B
πŸ’¬
ssmits/Qwen2.5-95B-Instruct
37.43
84.31
0.84
58.53
0.7
6.04
0.06
15.21
0.36
13.61
0.43
46.85
0.52
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
94
2
true
9c0e7df57a4fcf4d364efd916a0fc0abdd2d20a3
true
true
2024-09-26
2024-09-24
true
false
ssmits/Qwen2.5-95B-Instruct
1
ssmits/Qwen2.5-95B-Instruct (Merge)
🀝
mlabonne/BigQwen2.5-52B-Instruct
37.42
79.29
0.79
59.81
0.71
17.82
0.18
6.94
0.3
10.45
0.41
50.22
0.55
🀝 base merges and moerges
Qwen2ForCausalLM
Original
bfloat16
false
apache-2.0
52
2
true
425b9bffc9871085cc0d42c34138ce776f96ba02
true
true
2024-09-25
2024-09-23
true
true
mlabonne/BigQwen2.5-52B-Instruct
1
mlabonne/BigQwen2.5-52B-Instruct (Merge)
πŸ’¬
NousResearch/Hermes-3-Llama-3.1-70B
37.31
76.61
0.77
53.77
0.68
13.75
0.14
14.88
0.36
23.43
0.49
41.41
0.47
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
82
true
093242c69a91f8d9d5b8094c380b88772f9bd7f8
true
true
2024-08-28
2024-07-29
true
true
NousResearch/Hermes-3-Llama-3.1-70B
1
meta-llama/Meta-Llama-3.1-70B
πŸ’¬
MaziyarPanahi/calme-2.3-llama3-70b
36.84
80.1
0.8
48.01
0.64
21.9
0.22
11.74
0.34
12.57
0.43
46.72
0.52
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
3
true
bd17453eaae0e36d1e1e17da13fdd155fce91a29
true
true
2024-08-30
2024-04-27
true
false
MaziyarPanahi/calme-2.3-llama3-70b
2
meta-llama/Meta-Llama-3-70B
πŸ”Ά
ValiantLabs/Llama3-70B-Fireplace
36.82
77.74
0.78
49.56
0.65
19.64
0.2
13.98
0.35
16.77
0.44
43.25
0.49
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
llama3
70
3
true
220079e4115733991eb19c30d5480db9696a665e
true
true
2024-06-26
2024-05-09
true
false
ValiantLabs/Llama3-70B-Fireplace
0
ValiantLabs/Llama3-70B-Fireplace
πŸ”Ά
BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B
36.79
73.35
0.73
52.5
0.67
21.07
0.21
16.78
0.38
16.97
0.45
40.08
0.46
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
14
true
1ef63c4993a8c723c9695c827295c17080a64435
true
true
2024-09-26
2024-07-25
true
false
BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B
0
BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B
πŸ’¬
tenyx/Llama3-TenyxChat-70B
36.54
80.87
0.81
49.62
0.65
22.66
0.23
6.82
0.3
12.52
0.43
46.78
0.52
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
63
true
a85d31e3af8fcc847cc9169f1144cf02f5351fab
true
true
2024-08-04
2024-04-26
true
false
tenyx/Llama3-TenyxChat-70B
0
tenyx/Llama3-TenyxChat-70B
πŸ’¬
MaziyarPanahi/calme-2.2-llama3.1-70b
36.39
85.93
0.86
54.21
0.68
2.11
0.02
9.96
0.32
17.07
0.45
49.05
0.54
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
null
70
2
false
c81ac05ed2c2344e9fd366cfff197da406ef5234
true
true
2024-09-09
2024-09-09
true
false
MaziyarPanahi/calme-2.2-llama3.1-70b
2
meta-llama/Meta-Llama-3.1-70B
🀝
gbueno86/Brinebreath-Llama-3.1-70B
36.29
55.33
0.55
55.46
0.69
29.98
0.3
12.86
0.35
17.49
0.45
46.62
0.52
🀝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
llama3.1
70
1
true
c508ecf356167e8c498c6fa3937ba30a82208983
true
true
2024-08-29
2024-08-23
true
false
gbueno86/Brinebreath-Llama-3.1-70B
1
gbueno86/Brinebreath-Llama-3.1-70B (Merge)
πŸ’¬
meta-llama/Meta-Llama-3-70B-Instruct
36.18
80.99
0.81
50.19
0.65
23.34
0.23
4.92
0.29
10.92
0.42
46.74
0.52
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
1,415
true
7129260dd854a80eb10ace5f61c20324b472b31c
true
true
2024-06-12
2024-04-17
true
true
meta-llama/Meta-Llama-3-70B-Instruct
1
meta-llama/Meta-Llama-3-70B
πŸ’¬
Qwen/Qwen2.5-32B-Instruct
36.17
83.46
0.83
56.49
0.69
0
0
11.74
0.34
13.5
0.43
51.85
0.57
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
32
99
true
70e8dfb9ad18a7d499f765fe206ff065ed8ca197
true
true
2024-09-19
2024-09-17
true
true
Qwen/Qwen2.5-32B-Instruct
1
Qwen/Qwen2.5-32B
πŸ”Ά
flammenai/Mahou-1.5-llama3.1-70B
36.04
71.47
0.71
52.37
0.67
13.14
0.13
13.87
0.35
23.71
0.5
41.66
0.47
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
4
true
49f45cc4c21e2ba7ed5c5e71f90ffd0bd9169e2d
true
true
2024-10-14
2024-10-14
true
false
flammenai/Mahou-1.5-llama3.1-70B
1
flammenai/Mahou-1.5-llama3.1-70B (Merge)
🀝
nisten/franqwenstein-35b
35.94
37.99
0.38
52.23
0.66
30.29
0.3
20.47
0.4
22.12
0.49
52.56
0.57
🀝 base merges and moerges
Qwen2ForCausalLM
Original
float16
true
mit
34
5
true
7180aa73e82945a1d2ae0eb304508e21d57e4c27
true
true
2024-10-03
2024-10-03
false
false
nisten/franqwenstein-35b
1
nisten/franqwenstein-35b (Merge)
πŸ”Ά
rombodawg/Rombos-LLM-V2.6-Qwen-14b
35.89
52.14
0.52
49.22
0.65
28.85
0.29
17
0.38
19.26
0.48
48.85
0.54
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
14
26
true
887910d75a1837b8b8c7c3e50a257517d286ec60
true
true
2024-10-13
2024-10-12
false
false
rombodawg/Rombos-LLM-V2.6-Qwen-14b
1
rombodawg/Rombos-LLM-V2.6-Qwen-14b (Merge)
πŸ”Ά
BAAI/Infinity-Instruct-3M-0625-Llama3-70B
35.88
74.42
0.74
52.03
0.67
16.31
0.16
14.32
0.36
18.34
0.46
39.85
0.46
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
apache-2.0
70
3
true
6d8ceada57e55cff3503191adc4d6379ff321fe2
true
true
2024-08-30
2024-07-09
true
false
BAAI/Infinity-Instruct-3M-0625-Llama3-70B
0
BAAI/Infinity-Instruct-3M-0625-Llama3-70B
πŸ”Ά
KSU-HW-SEC/Llama3-70b-SVA-FT-1415
35.8
61.8
0.62
51.33
0.67
20.09
0.2
16.67
0.38
17.8
0.46
47.14
0.52
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
1c09728455567898116d2d9cfb6cbbbbd4ee730c
true
true
2024-09-08
null
false
false
KSU-HW-SEC/Llama3-70b-SVA-FT-1415
0
Removed
πŸ”Ά
failspy/llama-3-70B-Instruct-abliterated
35.79
80.23
0.8
48.94
0.65
23.72
0.24
5.26
0.29
10.53
0.41
46.06
0.51
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3
70
87
true
53ae9dafe8b3d163e05d75387575f8e9f43253d0
true
true
2024-07-03
2024-05-07
true
false
failspy/llama-3-70B-Instruct-abliterated
0
failspy/llama-3-70B-Instruct-abliterated
πŸ’¬
dnhkng/RYS-Llama-3-Large-Instruct
35.78
80.51
0.81
49.67
0.65
21.83
0.22
5.26
0.29
11.45
0.42
45.97
0.51
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
mit
73
1
true
01e3208aaf7bf6d2b09737960c701ec6628977fe
true
true
2024-08-07
2024-08-06
true
false
dnhkng/RYS-Llama-3-Large-Instruct
0
dnhkng/RYS-Llama-3-Large-Instruct
πŸ”Ά
KSU-HW-SEC/Llama3-70b-SVA-FT-final
35.78
61.65
0.62
51.33
0.67
20.09
0.2
16.67
0.38
17.8
0.46
47.14
0.52
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
391bbd94173b34975d1aa2c7356977a630253b75
true
true
2024-09-08
null
false
false
KSU-HW-SEC/Llama3-70b-SVA-FT-final
0
Removed
πŸ’¬
tanliboy/lambda-qwen2.5-32b-dpo-test
35.75
80.84
0.81
54.41
0.68
0
0
14.21
0.36
13.33
0.43
51.74
0.57
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
32
3
true
675b60d6e859455a6139e6e284bbe1844b8ddf46
true
true
2024-09-30
2024-09-22
true
false
tanliboy/lambda-qwen2.5-32b-dpo-test
2
Qwen/Qwen2.5-32B
πŸ”Ά
flammenai/Llama3.1-Flammades-70B
35.74
70.58
0.71
52.55
0.67
13.37
0.13
13.87
0.35
22.35
0.49
41.69
0.48
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
1
true
48909a734460e667e3a7e91bd25f124ec3b2ba74
true
true
2024-10-13
2024-10-12
true
false
flammenai/Llama3.1-Flammades-70B
1
flammenai/Llama3.1-Flammades-70B (Merge)
πŸ”Ά
mlabonne/Hermes-3-Llama-3.1-70B-lorablated
35.7
71.44
0.71
52.34
0.66
13.82
0.14
13.2
0.35
22.02
0.48
41.37
0.47
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
false
null
70
16
true
4303ff3b524418e9aa5e787d60595a44a6173b02
true
true
2024-10-12
2024-08-16
true
true
mlabonne/Hermes-3-Llama-3.1-70B-lorablated
1
mlabonne/Hermes-3-Llama-3.1-70B-lorablated (Merge)
πŸ”Ά
nbeerbower/Llama3.1-Gutenberg-Doppel-70B
35.68
70.92
0.71
52.56
0.67
13.75
0.14
12.64
0.34
22.68
0.49
41.52
0.47
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
3
true
5de156e97f776ce1b88ce5b2e2dc1e7709205a82
true
true
2024-10-12
2024-10-11
true
false
nbeerbower/Llama3.1-Gutenberg-Doppel-70B
1
nbeerbower/Llama3.1-Gutenberg-Doppel-70B (Merge)
πŸ”Ά
KSU-HW-SEC/Llama3-70b-SVA-FT-500
35.61
61.05
0.61
51.89
0.67
19.34
0.19
17.45
0.38
16.99
0.45
46.97
0.52
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
856a23f28aeada23d1135c86a37e05524307e8ed
true
true
2024-09-08
null
false
false
KSU-HW-SEC/Llama3-70b-SVA-FT-500
0
Removed
πŸ”Ά
cognitivecomputations/dolphin-2.9.2-qwen2-72b
35.42
63.44
0.63
47.7
0.63
18.66
0.19
16
0.37
17.04
0.45
49.68
0.55
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
other
72
60
true
e79582577c2bf2af304221af0e8308b7e7d46ca1
true
true
2024-10-20
2024-05-27
true
true
cognitivecomputations/dolphin-2.9.2-qwen2-72b
1
Qwen/Qwen2-72B
πŸ”Ά
cloudyu/Llama-3-70Bx2-MOE
35.35
54.82
0.55
51.42
0.66
19.86
0.2
19.13
0.39
20.85
0.48
46.02
0.51
πŸ”Ά fine-tuned on domain-specific datasets
MixtralForCausalLM
Original
bfloat16
true
llama3
126
1
true
b8bd85e8db8e4ec352b93441c92e0ae1334bf5a7
true
false
2024-06-27
2024-05-20
false
false
cloudyu/Llama-3-70Bx2-MOE
0
cloudyu/Llama-3-70Bx2-MOE
πŸ”Ά
Sao10K/L3-70B-Euryale-v2.1
35.35
73.84
0.74
48.7
0.65
20.85
0.21
10.85
0.33
12.25
0.42
45.6
0.51
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
cc-by-nc-4.0
70
115
true
36ad832b771cd783ea7ad00ed39e61f679b1a7c6
true
true
2024-07-01
2024-06-11
true
false
Sao10K/L3-70B-Euryale-v2.1
0
Sao10K/L3-70B-Euryale-v2.1
🀝
allknowingroger/Qwenslerp2-14B
35.32
50.07
0.5
50.3
0.66
27.95
0.28
15.77
0.37
18.88
0.47
48.92
0.54
🀝 base merges and moerges
Qwen2ForCausalLM
Original
bfloat16
false
apache-2.0
14
1
true
38e902c114b5640509a8615fc2a2546e07a5fb3f
true
true
2024-10-21
2024-10-19
false
false
allknowingroger/Qwenslerp2-14B
1
allknowingroger/Qwenslerp2-14B (Merge)
πŸ’¬
OpenBuddy/openbuddy-llama3.1-70b-v22.1-131k
35.23
73.33
0.73
51.94
0.67
3.4
0.03
16.67
0.38
18.24
0.46
47.82
0.53
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
other
70
1
true
43ed945180174d79a8f6c68509161c249c884dfa
true
true
2024-08-24
2024-08-21
true
false
OpenBuddy/openbuddy-llama3.1-70b-v22.1-131k
0
OpenBuddy/openbuddy-llama3.1-70b-v22.1-131k
🀝
allknowingroger/Qwenslerp3-14B
35.21
50.52
0.51
49.81
0.65
27.42
0.27
16.67
0.38
18.02
0.47
48.83
0.54
🀝 base merges and moerges
Qwen2ForCausalLM
Original
bfloat16
false
apache-2.0
14
1
true
ac60a6c4e224e5b52c42bebfd0cf81f920befdef
true
true
2024-10-21
2024-10-19
false
false
allknowingroger/Qwenslerp3-14B
1
allknowingroger/Qwenslerp3-14B (Merge)
πŸ”Ά
migtissera/Llama-3-70B-Synthia-v3.5
35.2
60.76
0.61
49.12
0.65
18.96
0.19
18.34
0.39
23.39
0.49
40.65
0.47
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
llama3
70
5
true
8744db0bccfc18f1847633da9d29fc89b35b4190
true
true
2024-08-28
2024-05-26
true
false
migtissera/Llama-3-70B-Synthia-v3.5
0
migtissera/Llama-3-70B-Synthia-v3.5
πŸ’¬
OpenBuddy/openbuddy-llama3-70b-v21.2-32k
35.18
70.1
0.7
49.97
0.65
18.05
0.18
12.3
0.34
18.05
0.46
42.58
0.48
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
other
70
1
true
e79a2f16c052fc76eeafb5b51d16261b2b981d0f
true
true
2024-09-05
2024-06-12
true
false
OpenBuddy/openbuddy-llama3-70b-v21.2-32k
0
OpenBuddy/openbuddy-llama3-70b-v21.2-32k
🟒
Qwen/Qwen2-72B
35.13
38.24
0.38
51.86
0.66
29.15
0.29
19.24
0.39
19.73
0.47
52.56
0.57
🟒 pretrained
Qwen2ForCausalLM
Original
bfloat16
true
other
72
189
true
87993795c78576318087f70b43fbf530eb7789e7
true
true
2024-06-26
2024-05-22
false
true
Qwen/Qwen2-72B
0
Qwen/Qwen2-72B
πŸ”Ά
Sao10K/L3-70B-Euryale-v2.1
35.11
72.81
0.73
49.19
0.65
20.24
0.2
10.85
0.33
12.05
0.42
45.51
0.51
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
cc-by-nc-4.0
70
115
true
36ad832b771cd783ea7ad00ed39e61f679b1a7c6
true
true
2024-06-26
2024-06-11
true
false
Sao10K/L3-70B-Euryale-v2.1
0
Sao10K/L3-70B-Euryale-v2.1
πŸ’¬
microsoft/Phi-3.5-MoE-instruct
35.1
69.25
0.69
48.77
0.64
20.54
0.21
14.09
0.36
17.33
0.46
40.64
0.47
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Phi3ForCausalLM
Original
bfloat16
true
mit
42
504
true
482a9ba0eb0e1fa1671e3560e009d7cec2e5147c
true
false
2024-08-21
2024-08-17
true
true
microsoft/Phi-3.5-MoE-instruct
0
microsoft/Phi-3.5-MoE-instruct
πŸ’¬
Qwen/Qwen2-Math-72B-Instruct
34.79
56.94
0.57
47.96
0.63
35.95
0.36
15.77
0.37
15.73
0.45
36.36
0.43
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
83
true
5c267882f3377bcfc35882f8609098a894eeeaa8
true
true
2024-08-19
2024-08-08
true
true
Qwen/Qwen2-Math-72B-Instruct
0
Qwen/Qwen2-Math-72B-Instruct
πŸ”Ά
aaditya/Llama3-OpenBioLLM-70B
34.73
75.97
0.76
47.15
0.64
18.2
0.18
9.73
0.32
14.35
0.44
42.97
0.49
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3
70
340
true
5f79deaf38bc5f662943d304d59cb30357e8e5bd
true
true
2024-08-30
2024-04-24
true
false
aaditya/Llama3-OpenBioLLM-70B
2
meta-llama/Meta-Llama-3-70B
πŸ’¬
abacusai/Smaug-Llama-3-70B-Instruct-32K
34.72
77.61
0.78
49.07
0.65
21.22
0.21
6.15
0.3
12.43
0.42
41.83
0.48
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
21
true
33840982dc253968f32ef3a534ee0e025eb97482
true
true
2024-08-06
2024-06-11
true
true
abacusai/Smaug-Llama-3-70B-Instruct-32K
0
abacusai/Smaug-Llama-3-70B-Instruct-32K
πŸ”Ά
dnhkng/RYS-XLarge2
34.7
49.02
0.49
51.55
0.66
25.38
0.25
16.55
0.37
17.05
0.45
48.65
0.54
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
null
77
0
false
3ce16c9427e93e09ce10a28fa644469d49a51113
true
true
2024-10-11
null
true
false
dnhkng/RYS-XLarge2
0
Removed
πŸ”Ά
rombodawg/Rombos-LLM-V2.5-Qwen-14b
34.52
58.4
0.58
49.39
0.65
15.63
0.16
16.22
0.37
18.83
0.47
48.62
0.54
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
14
5
true
834ddb1712ae6d1b232b2d5b26be658d90d23e43
true
true
2024-09-29
2024-10-06
false
false
rombodawg/Rombos-LLM-V2.5-Qwen-14b
1
rombodawg/Rombos-LLM-V2.5-Qwen-14b (Merge)
πŸ”Ά
BAAI/Infinity-Instruct-3M-0613-Llama3-70B
34.47
68.21
0.68
51.33
0.66
14.88
0.15
14.43
0.36
16.53
0.45
41.44
0.47
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
70
5
true
9fc53668064bdda22975ca72c5a287f8241c95b3
true
true
2024-06-28
2024-06-27
true
false
BAAI/Infinity-Instruct-3M-0613-Llama3-70B
0
BAAI/Infinity-Instruct-3M-0613-Llama3-70B
πŸ’¬
dnhkng/RYS-Llama-3-Huge-Instruct
34.37
76.86
0.77
49.07
0.65
21.22
0.21
1.45
0.26
11.93
0.42
45.66
0.51
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
mit
99
1
true
cfe14a5339e88a7a89f075d9d48215d45f64acaf
true
true
2024-08-07
2024-08-06
true
false
dnhkng/RYS-Llama-3-Huge-Instruct
0
dnhkng/RYS-Llama-3-Huge-Instruct
πŸ’¬
MaziyarPanahi/calme-2.1-llama3.1-70b
34.34
84.34
0.84
48.55
0.64
1.44
0.01
10.4
0.33
13.72
0.44
47.58
0.53
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
null
70
4
false
f39ad1c90b0f30379e80756d29c6533cf84c362a
true
true
2024-07-24
2024-07-23
true
false
MaziyarPanahi/calme-2.1-llama3.1-70b
2
meta-llama/Meta-Llama-3.1-70B
πŸ’¬
nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
34.29
73.81
0.74
47.11
0.63
26.96
0.27
1.12
0.26
13.2
0.43
43.54
0.49
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
1,038
true
250db5cf2323e04a6d2025a2ca2b94a95c439e88
true
true
2024-10-16
2024-10-12
true
true
nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
2
meta-llama/Meta-Llama-3.1-70B
πŸ”Ά
nisten/franqwenstein-35b
34.16
39.14
0.39
51.68
0.66
28.7
0.29
14.54
0.36
19.68
0.47
51.23
0.56
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
mit
34
5
true
901351a987d664a1cd7f483115a167d3ae5694ec
true
true
2024-10-03
2024-10-03
true
false
nisten/franqwenstein-35b
1
nisten/franqwenstein-35b (Merge)
πŸ’¬
mistralai/Mixtral-8x22B-Instruct-v0.1
33.89
71.84
0.72
44.11
0.61
18.73
0.19
16.44
0.37
13.49
0.43
38.7
0.45
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
MixtralForCausalLM
Original
bfloat16
true
apache-2.0
140
679
true
b0c3516041d014f640267b14feb4e9a84c8e8c71
true
false
2024-06-12
2024-04-16
true
true
mistralai/Mixtral-8x22B-Instruct-v0.1
1
mistralai/Mixtral-8x22B-v0.1
🀝
allknowingroger/Qwen2.5-slerp-14B
33.87
49.28
0.49
49.79
0.65
20.47
0.2
15.66
0.37
19.37
0.47
48.66
0.54
🀝 base merges and moerges
Qwen2ForCausalLM
Original
bfloat16
false
apache-2.0
14
0
true
a44b0ea8291b62785152c2fe6ab336f5da672d1e
true
true
2024-10-21
2024-10-17
false
false
allknowingroger/Qwen2.5-slerp-14B
1
allknowingroger/Qwen2.5-slerp-14B (Merge)
πŸ’¬
arcee-ai/SuperNova-Medius
33.78
71.99
0.72
48.01
0.64
14.5
0.15
11.07
0.33
12.28
0.42
44.83
0.5
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
false
apache-2.0
14
139
true
e34fafcac2801be1ae5c7eb744e191a08119f2af
true
true
2024-10-22
2024-10-02
true
false
arcee-ai/SuperNova-Medius
1
arcee-ai/SuperNova-Medius (Merge)
πŸ’¬
HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1
33.77
65.11
0.65
47.5
0.63
18.35
0.18
17.11
0.38
14.72
0.45
39.85
0.46
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
MixtralForCausalLM
Original
float16
true
apache-2.0
140
260
true
a3be084543d278e61b64cd600f28157afc79ffd3
true
true
2024-06-12
2024-04-10
true
true
HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1
1
mistral-community/Mixtral-8x22B-v0.1
πŸ”Ά
nbeerbower/Llama-3.1-Nemotron-lorablated-70B
33.69
71.47
0.71
48.06
0.64
23.34
0.23
0.89
0.26
14.92
0.44
43.46
0.49
πŸ”Ά fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
false
llama3.1
70
2
true
f335a582cdb7fb0e63a7343a908766ebd0ed9882
true
true
2024-10-18
2024-10-17
true
false
nbeerbower/Llama-3.1-Nemotron-lorablated-70B
1
nbeerbower/Llama-3.1-Nemotron-lorablated-70B (Merge)
🀝
Lambent/qwen2.5-reinstruct-alternate-lumen-14B
33.66
47.94
0.48
48.99
0.65
19.79
0.2
16.89
0.38
19.62
0.48
48.76
0.54
🀝 base merges and moerges
Qwen2ForCausalLM
Original
bfloat16
true
null
14
3
false
dac3be334098338fb6c02636349e8ed53f18c4a4
true
true
2024-09-28
2024-09-23
false
false
Lambent/qwen2.5-reinstruct-alternate-lumen-14B
1
Lambent/qwen2.5-reinstruct-alternate-lumen-14B (Merge)
πŸ’¬
tanliboy/lambda-qwen2.5-14b-dpo-test
33.52
82.31
0.82
48.45
0.64
0
0
14.99
0.36
12.59
0.43
42.75
0.48
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
14
6
true
96607eea3c67f14f73e576580610dba7530c5dd9
true
true
2024-09-20
2024-09-20
true
false
tanliboy/lambda-qwen2.5-14b-dpo-test
2
Qwen/Qwen2.5-14B
πŸ’¬
CohereForAI/c4ai-command-r-plus-08-2024
33.42
75.4
0.75
42.84
0.6
11.03
0.11
13.42
0.35
19.84
0.48
38.01
0.44
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
CohereForCausalLM
Original
float16
true
cc-by-nc-4.0
103
152
true
2d8cf3ab0af78b9e43546486b096f86adf3ba4d0
true
true
2024-09-19
2024-08-21
true
true
CohereForAI/c4ai-command-r-plus-08-2024
0
CohereForAI/c4ai-command-r-plus-08-2024
🀝
v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
33.39
48.55
0.49
49.74
0.65
19.71
0.2
15.21
0.36
18.43
0.47
48.68
0.54
🀝 base merges and moerges
Qwen2ForCausalLM
Original
bfloat16
false
apache-2.0
14
4
true
1069abb4c25855e67ffaefa08a0befbb376e7ca7
true
true
2024-09-28
2024-09-20
false
false
v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
1
v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno (Merge)
🀝
zelk12/MT1-gemma-2-9B
33.37
79.47
0.79
44.16
0.61
13.37
0.13
12.75
0.35
13.16
0.43
37.31
0.44
🀝 base merges and moerges
Gemma2ForCausalLM
Original
bfloat16
true
null
10
1
false
3a5e77518ca9c3c8ea2edac4c03bc220ee91f3ed
true
true
2024-10-14
2024-10-12
true
false
zelk12/MT1-gemma-2-9B
1
zelk12/MT1-gemma-2-9B (Merge)
πŸ’¬
jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
33.3
68.52
0.69
49.85
0.64
17.98
0.18
10.07
0.33
12.35
0.43
41.07
0.47
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Phi3ForCausalLM
Original
float16
true
mit
13
10
true
d34bbd55b48e553f28579d86f3ccae19726c6b39
true
true
2024-08-28
2024-08-12
true
false
jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
0
jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
πŸ”Ά
migtissera/Tess-v2.5.2-Qwen2-72B
33.28
44.94
0.45
52.31
0.66
27.42
0.27
13.42
0.35
10.89
0.42
50.68
0.56
πŸ”Ά fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
other
72
11
true
0435e634ad9bc8b1172395a535b78e6f25f3594f
true
true
2024-08-10
2024-06-13
true
false
migtissera/Tess-v2.5.2-Qwen2-72B
0
migtissera/Tess-v2.5.2-Qwen2-72B
🀝
zelk12/MT4-gemma-2-9B
33.16
77.62
0.78
43.55
0.61
15.63
0.16
11.74
0.34
13
0.43
37.4
0.44
🀝 base merges and moerges
Gemma2ForCausalLM
Original
bfloat16
true
null
10
0
false
2167ea02baf9145a697a7d828a17c75b86e5e282
true
true
2024-10-20
2024-10-16
true
false
zelk12/MT4-gemma-2-9B
1
zelk12/MT4-gemma-2-9B (Merge)
πŸ’¬
TheTsar1209/qwen-carpmuscle-v0.2
33.11
52.57
0.53
48.18
0.64
25
0.25
14.09
0.36
12.75
0.43
46.08
0.51
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
apache-2.0
14
0
true
081f6b067ebca9bc384af283f1d267880534b8e3
true
true
2024-10-19
2024-10-16
true
false
TheTsar1209/qwen-carpmuscle-v0.2
3
Qwen/Qwen2.5-14B
🀝
zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25
33.06
77.07
0.77
43.85
0.61
14.12
0.14
12.42
0.34
13.13
0.43
37.78
0.44
🀝 base merges and moerges
Gemma2ForCausalLM
Original
bfloat16
true
null
10
1
false
e652c9e07265526851dad994f4640aa265b9ab56
true
true
2024-10-04
2024-10-04
true
false
zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25
1
zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25 (Merge)
🀝
zelk12/MT2-gemma-2-9B
33.03
78.86
0.79
44.17
0.61
13.22
0.13
12.98
0.35
11.54
0.42
37.43
0.44
🀝 base merges and moerges
Gemma2ForCausalLM
Original
bfloat16
true
null
10
1
false
d20d7169ce0f53d586504c50b4b7dc470bf8a781
true
true
2024-10-15
2024-10-14
true
false
zelk12/MT2-gemma-2-9B
1
zelk12/MT2-gemma-2-9B (Merge)
πŸ’¬
microsoft/Phi-3-medium-4k-instruct
32.67
64.23
0.64
49.38
0.64
16.99
0.17
11.52
0.34
13.05
0.43
40.84
0.47
πŸ’¬ chat models (RLHF, DPO, IFT, ...)
Phi3ForCausalLM
Original
bfloat16
true
mit
13
211
true
d194e4e74ffad5a5e193e26af25bcfc80c7f1ffc
true
true
2024-06-12
2024-05-07
true
true
microsoft/Phi-3-medium-4k-instruct
0
microsoft/Phi-3-medium-4k-instruct
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