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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.prefill.latency.unit', 'report.prefill.memory.max_allocated', 'config.launcher._target_', 'report.load.energy.ram', 'config.backend.cache_implementation', 'report.per_token.throughput.unit', 'config.environment.diffusers_commit', 'config.backend.seed', 'config.environment.platform', 'config.environment.processor', 'report.prefill.throughput.value', 'report.prefill.memory.max_process_vram', 'config.backend.version', 'report.decode.throughput.unit', 'config.environment.transformers_version', 'report.per_token.efficiency', 'report.prefill.latency.p50', 'config.environment.peft_version', 'report.load.memory.max_allocated', 'config.backend.quantization_config.version', 'report.decode.memory.max_allocated', 'report.decode.memory.max_global_vram', 'config.scenario.new_tokens', 'config.backend.hub_kwargs.local_files_only', 'report.load.energy.cpu', 'report.prefill.throughput.unit', 'report.decode.energy.gpu', 'report.decode.latency.unit', 'config.environment.accelerate_version', 'report.prefill.energy.gpu', 'config.launcher.numactl', 'report.load.memory.max_ram', 'report.decode.efficiency.value', 'report.load.latency.p50', 'config.scenario.name', 'report.decode.throughput.value', 'config.backend.task', 'report.decode.energy.total', 'config.backend.hub_kwargs.force_download', 'config.environment.timm_version', 'report.decode.latency.mean', 'config.backend.model_type', 'config.environment.gpu', 'report.prefill.memory.unit', 'report.prefill.latency.values', 'report.load.efficie
...
'config.environment.optimum_commit', 'report.load.latency.total', 'config.scenario.input_shapes.sequence_length', 'config.backend.library', 'report.decode.latency.stdev', 'config.backend.autocast_enabled', 'config.environment.peft_commit', 'config.scenario.input_shapes.num_choices', 'config.backend.processor', 'report.decode.latency.p90', 'config.scenario.memory', 'report.prefill.energy.total', 'report.prefill.latency.count', 'report.per_token.latency.mean', 'report.decode.memory.max_process_vram', 'config.environment.cpu', 'report.prefill.memory.max_global_vram', 'config.backend.attn_implementation', 'report.traceback', 'report.per_token.latency.p99', 'report.per_token.latency.total', 'report.decode.latency.p95', 'config.environment.cpu_count', 'report.load.throughput', 'config.environment.transformers_commit', 'config.scenario.latency', 'report.decode.latency.total', 'config.environment.optimum_version', 'report.prefill.latency.total', 'config.environment.timm_commit', 'config.scenario.generate_kwargs.max_new_tokens', 'report.load.memory.max_global_vram', 'config.backend.inter_op_num_threads', 'report.load.energy.total', 'config.name', 'report.prefill.memory.max_ram', 'config.launcher.device_isolation', 'config.backend.deepspeed_inference', 'report.prefill.energy.ram', 'report.prefill.efficiency.value', 'config.backend.quantization_config.exllama_config.max_batch_size', 'config.backend.torch_compile_target', 'report.load.memory.max_reserved', 'report.decode.memory.max_ram'}) and 34 missing columns ({'Hub ❤️', 'Base Model', 'Weight type', 'MATH Lvl 5', 'Model sha', 'Not_Merged', 'Generation', 'GPQA', 'fullname', 'Chat Template', 'MoE', 'BBH Raw', 'Available on the hub', 'IFEval Raw', 'Model', 'GPQA Raw', '#Params (B)', 'BBH', 'MUSR', 'Hub License', "Maintainer's Highlight", 'Submission Date', 'MMLU-PRO', 'Flagged', 'MUSR Raw', 'Precision', 'Type', 'Upload To Hub Date', 'Average ⬆️', 'T', 'IFEval', 'MMLU-PRO Raw', 'Architecture', 'MATH Lvl 5 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 c7cee487ad0aef4959407cce4f69477c1545ab4f)

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 2013, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, 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: 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.processor_kwargs.trust_remote_code: bool
              config.backend.hub_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.deepspeed_inference: bool
              config.backend.peft_type: double
              config.scenario.name: string
              config.scenario._target_: string
              config.scenario.iterations: int64
              config.scenario.duration: int64
              config.scenario.warmup_runs: int64
              config.scenario.input_shapes.batch_size: int64
              config.scenario.input_shapes.num_choices: int64
              co
              ...
              .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
              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.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 1396, 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 1045, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, 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 1884, 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 2015, 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.prefill.latency.unit', 'report.prefill.memory.max_allocated', 'config.launcher._target_', 'report.load.energy.ram', 'config.backend.cache_implementation', 'report.per_token.throughput.unit', 'config.environment.diffusers_commit', 'config.backend.seed', 'config.environment.platform', 'config.environment.processor', 'report.prefill.throughput.value', 'report.prefill.memory.max_process_vram', 'config.backend.version', 'report.decode.throughput.unit', 'config.environment.transformers_version', 'report.per_token.efficiency', 'report.prefill.latency.p50', 'config.environment.peft_version', 'report.load.memory.max_allocated', 'config.backend.quantization_config.version', 'report.decode.memory.max_allocated', 'report.decode.memory.max_global_vram', 'config.scenario.new_tokens', 'config.backend.hub_kwargs.local_files_only', 'report.load.energy.cpu', 'report.prefill.throughput.unit', 'report.decode.energy.gpu', 'report.decode.latency.unit', 'config.environment.accelerate_version', 'report.prefill.energy.gpu', 'config.launcher.numactl', 'report.load.memory.max_ram', 'report.decode.efficiency.value', 'report.load.latency.p50', 'config.scenario.name', 'report.decode.throughput.value', 'config.backend.task', 'report.decode.energy.total', 'config.backend.hub_kwargs.force_download', 'config.environment.timm_version', 'report.decode.latency.mean', 'config.backend.model_type', 'config.environment.gpu', 'report.prefill.memory.unit', 'report.prefill.latency.values', 'report.load.efficie
              ...
              'config.environment.optimum_commit', 'report.load.latency.total', 'config.scenario.input_shapes.sequence_length', 'config.backend.library', 'report.decode.latency.stdev', 'config.backend.autocast_enabled', 'config.environment.peft_commit', 'config.scenario.input_shapes.num_choices', 'config.backend.processor', 'report.decode.latency.p90', 'config.scenario.memory', 'report.prefill.energy.total', 'report.prefill.latency.count', 'report.per_token.latency.mean', 'report.decode.memory.max_process_vram', 'config.environment.cpu', 'report.prefill.memory.max_global_vram', 'config.backend.attn_implementation', 'report.traceback', 'report.per_token.latency.p99', 'report.per_token.latency.total', 'report.decode.latency.p95', 'config.environment.cpu_count', 'report.load.throughput', 'config.environment.transformers_commit', 'config.scenario.latency', 'report.decode.latency.total', 'config.environment.optimum_version', 'report.prefill.latency.total', 'config.environment.timm_commit', 'config.scenario.generate_kwargs.max_new_tokens', 'report.load.memory.max_global_vram', 'config.backend.inter_op_num_threads', 'report.load.energy.total', 'config.name', 'report.prefill.memory.max_ram', 'config.launcher.device_isolation', 'config.backend.deepspeed_inference', 'report.prefill.energy.ram', 'report.prefill.efficiency.value', 'config.backend.quantization_config.exllama_config.max_batch_size', 'config.backend.torch_compile_target', 'report.load.memory.max_reserved', 'report.decode.memory.max_ram'}) and 34 missing columns ({'Hub ❤️', 'Base Model', 'Weight type', 'MATH Lvl 5', 'Model sha', 'Not_Merged', 'Generation', 'GPQA', 'fullname', 'Chat Template', 'MoE', 'BBH Raw', 'Available on the hub', 'IFEval Raw', 'Model', 'GPQA Raw', '#Params (B)', 'BBH', 'MUSR', 'Hub License', "Maintainer's Highlight", 'Submission Date', 'MMLU-PRO', 'Flagged', 'MUSR Raw', 'Precision', 'Type', 'Upload To Hub Date', 'Average ⬆️', 'T', 'IFEval', 'MMLU-PRO Raw', 'Architecture', 'MATH Lvl 5 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 c7cee487ad0aef4959407cce4f69477c1545ab4f)
              
              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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
19
true
0a35e51ffa9efa644c11816a2d56434804177acb
true
true
2024-09-03
2024-08-07
true
false
MaziyarPanahi/calme-2.4-rys-78b
2
dnhkng/RYS-XLarge
🔶
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
🔶 fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
mit
77
61
true
0f84dd9dde60f383e1e2821496befb4ce9a11ef6
true
true
2024-08-07
2024-07-24
false
false
dnhkng/RYS-XLarge
0
dnhkng/RYS-XLarge
💬
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
💬 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
💬
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
💬 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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
25
true
0369c39770f45f2464587918f2dbdb8449ea3a0d
true
true
2024-06-26
2024-06-08
true
false
MaziyarPanahi/calme-2.1-qwen2-72b
2
Qwen/Qwen2-72B
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
4
true
529e9bd80a76d943409bc92bb246aa7ca63dd9e6
true
true
2024-08-06
2024-07-09
true
false
MaziyarPanahi/calme-2.2-qwen2-72b
1
Qwen/Qwen2-72B
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
3
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)
🔶
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
🔶 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)
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
659
true
1af63c698f59c4235668ec9c1395468cb7cd7e79
true
true
2024-06-26
2024-05-28
false
true
Qwen/Qwen2-72B-Instruct
1
Qwen/Qwen2-72B
🔶
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
🔶 fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
other
72
14
true
10cabc4beb57a69df51533f65e39a7ad22821370
true
true
2024-08-16
2024-08-14
true
true
abacusai/Dracarys-72B-Instruct
0
abacusai/Dracarys-72B-Instruct
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
11
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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
158
true
fef27e0f235ae8858b84b765db773a2a954110dd
true
true
2024-07-25
2024-06-17
true
false
alpindale/magnum-72b-v1
2
Qwen/Qwen2-72B
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3.1
70
480
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
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
mit
81
0
true
52cc979de78155b33689efa48f52a8aab184bd86
true
true
2024-08-22
2024-08-11
true
false
dnhkng/RYS-Llama3.1-Large
0
dnhkng/RYS-Llama3.1-Large
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
6
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
2024-06-26
2024-06-06
true
false
paulml/ECE-ILAB-Q1
0
paulml/ECE-ILAB-Q1
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
b195fea0d8f350ff29243d4e88654b1baa5af79e
true
true
2024-09-08
2024-09-08
false
false
KSU-HW-SEC/Llama3.1-70b-SVA-FT-1000step
0
KSU-HW-SEC/Llama3.1-70b-SVA-FT-1000step
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
SolarForCausalLM
Original
bfloat16
true
mit
22
298
true
b4db141b5fb08b23f8bc323bc34e2cff3e9675f8
true
true
2024-09-11
2024-09-09
true
true
upstage/solar-pro-preview-instruct
0
upstage/solar-pro-preview-instruct
🔶
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
🔶 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
🤝
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)
💬
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
💬 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
🔶
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
🔶 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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
75
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
🔶
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
🔶 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
💬
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
💬 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
🤝
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)
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
1,385
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
🔶
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
🔶 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
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
1c09728455567898116d2d9cfb6cbbbbd4ee730c
true
true
2024-09-08
2024-09-08
false
false
KSU-HW-SEC/Llama3-70b-SVA-FT-1415
0
KSU-HW-SEC/Llama3-70b-SVA-FT-1415
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3
70
82
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
💬
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
💬 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
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
391bbd94173b34975d1aa2c7356977a630253b75
true
true
2024-09-08
2024-09-08
false
false
KSU-HW-SEC/Llama3-70b-SVA-FT-final
0
KSU-HW-SEC/Llama3-70b-SVA-FT-final
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
null
70
0
false
856a23f28aeada23d1135c86a37e05524307e8ed
true
true
2024-09-08
2024-09-08
false
false
KSU-HW-SEC/Llama3-70b-SVA-FT-500
0
KSU-HW-SEC/Llama3-70b-SVA-FT-500
🔶
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
🔶 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
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
cc-by-nc-4.0
70
110
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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
other
70
0
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
🔶
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
🔶 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
🟢
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
181
true
87993795c78576318087f70b43fbf530eb7789e7
true
true
2024-06-26
2024-05-22
false
true
Qwen/Qwen2-72B
0
Qwen/Qwen2-72B
🔶
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
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
cc-by-nc-4.0
70
110
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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Phi3ForCausalLM
Original
bfloat16
true
mit
42
467
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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
20
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
🔶
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
🔶 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
💬
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
💬 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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
MixtralForCausalLM
Original
bfloat16
true
apache-2.0
140
661
true
b0c3516041d014f640267b14feb4e9a84c8e8c71
true
false
2024-06-12
2024-04-16
true
true
mistralai/Mixtral-8x22B-Instruct-v0.1
1
mistralai/Mixtral-8x22B-v0.1
💬
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
💬 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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Phi3ForCausalLM
Original
float16
true
mit
13
6
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
🔶
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
🔶 fine-tuned on domain-specific datasets
Qwen2ForCausalLM
Original
bfloat16
true
other
72
12
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
💬
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
💬 chat models (RLHF, DPO, IFT, ...)
Phi3ForCausalLM
Original
bfloat16
true
mit
13
207
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
💬
01-ai/Yi-1.5-34B-Chat
32.63
60.67
0.61
44.26
0.61
23.34
0.23
15.32
0.36
13.06
0.43
39.12
0.45
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
34
231
true
f3128b2d02d82989daae566c0a7eadc621ca3254
true
true
2024-06-12
2024-05-10
true
true
01-ai/Yi-1.5-34B-Chat
0
01-ai/Yi-1.5-34B-Chat
🔶
alpindale/WizardLM-2-8x22B
32.61
52.72
0.53
48.58
0.64
22.28
0.22
17.56
0.38
14.54
0.44
39.96
0.46
🔶 fine-tuned on domain-specific datasets
MixtralForCausalLM
Original
bfloat16
true
apache-2.0
140
376
true
087834da175523cffd66a7e19583725e798c1b4f
true
true
2024-06-28
2024-04-16
false
false
alpindale/WizardLM-2-8x22B
0
alpindale/WizardLM-2-8x22B
💬
google/gemma-2-27b-it
32.31
79.78
0.8
49.27
0.65
0.68
0.01
16.67
0.38
9.11
0.4
38.35
0.45
💬 chat models (RLHF, DPO, IFT, ...)
Gemma2ForCausalLM
Original
bfloat16
true
gemma
27
397
true
f6c533e5eb013c7e31fc74ef042ac4f3fb5cf40b
true
true
2024-08-07
2024-06-24
true
true
google/gemma-2-27b-it
1
google/gemma-2-27b
💬
MaziyarPanahi/calme-2.4-llama3-70b
32.18
50.27
0.5
48.4
0.64
22.66
0.23
11.97
0.34
13.1
0.43
46.71
0.52
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
13
true
cb03e4d810b82d86e7cb01ab146bade09a5d06d1
true
true
2024-06-26
2024-04-28
true
false
MaziyarPanahi/calme-2.4-llama3-70b
2
meta-llama/Meta-Llama-3-70B
🤝
paloalma/TW3-JRGL-v2
32.12
53.16
0.53
45.61
0.61
15.86
0.16
14.54
0.36
20.7
0.49
42.87
0.49
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
apache-2.0
72
0
true
aca3f0ba2bfb90038a9e2cd5b486821d4c181b46
true
true
2024-08-29
2024-04-01
false
false
paloalma/TW3-JRGL-v2
0
paloalma/TW3-JRGL-v2
💬
internlm/internlm2_5-20b-chat
32.08
70.1
0.7
62.83
0.75
0
0
9.51
0.32
16.74
0.46
33.31
0.4
💬 chat models (RLHF, DPO, IFT, ...)
InternLM2ForCausalLM
Original
bfloat16
true
other
19
76
true
ef17bde929761255fee76d95e2c25969ccd93b0d
true
true
2024-08-12
2024-07-30
true
true
internlm/internlm2_5-20b-chat
0
internlm/internlm2_5-20b-chat
💬
cognitivecomputations/dolphin-2.9.2-qwen2-72b
32
40.38
0.4
47.7
0.63
21.37
0.21
16
0.37
17.04
0.45
49.52
0.55
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
72
51
true
e79582577c2bf2af304221af0e8308b7e7d46ca1
true
true
2024-06-27
2024-05-27
true
true
cognitivecomputations/dolphin-2.9.2-qwen2-72b
1
Qwen/Qwen2-72B
💬
MTSAIR/MultiVerse_70B
31.73
52.49
0.52
46.14
0.62
16.16
0.16
13.87
0.35
18.82
0.47
42.89
0.49
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
other
72
38
true
063430cdc4d972a0884e3e3e3d45ea4afbdf71a2
true
true
2024-06-29
2024-03-25
false
false
MTSAIR/MultiVerse_70B
0
MTSAIR/MultiVerse_70B
🤝
paloalma/Le_Triomphant-ECE-TW3
31.66
54.02
0.54
44.96
0.61
17.45
0.17
13.2
0.35
18.5
0.47
41.81
0.48
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
apache-2.0
72
3
true
f72399253bb3e65c0f55e50461488c098f658a49
true
true
2024-07-25
2024-04-01
false
false
paloalma/Le_Triomphant-ECE-TW3
0
paloalma/Le_Triomphant-ECE-TW3
🔶
failspy/Phi-3-medium-4k-instruct-abliterated-v3
31.55
63.19
0.63
46.73
0.63
14.12
0.14
8.95
0.32
18.52
0.46
37.78
0.44
🔶 fine-tuned on domain-specific datasets
Phi3ForCausalLM
Original
bfloat16
true
mit
13
22
true
959b09eacf6cae85a8eb21b25e998addc89a367b
true
true
2024-07-29
2024-05-22
true
false
failspy/Phi-3-medium-4k-instruct-abliterated-v3
0
failspy/Phi-3-medium-4k-instruct-abliterated-v3
💬
microsoft/Phi-3-medium-128k-instruct
31.52
60.4
0.6
48.46
0.64
16.16
0.16
11.52
0.34
11.35
0.41
41.24
0.47
💬 chat models (RLHF, DPO, IFT, ...)
Phi3ForCausalLM
Original
bfloat16
true
mit
13
361
true
fa7d2aa4f5ea69b2e36b20d050cdae79c9bfbb3f
true
true
2024-08-21
2024-05-07
true
true
microsoft/Phi-3-medium-128k-instruct
0
microsoft/Phi-3-medium-128k-instruct
💬
Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO
31.42
47.99
0.48
51.03
0.65
17.45
0.17
10.18
0.33
20.53
0.48
41.37
0.47
💬 chat models (RLHF, DPO, IFT, ...)
MistralForCausalLM
Original
float16
true
mit
13
3
true
b749dbcb19901b8fd0e9f38c923a24533569f895
true
true
2024-08-13
2024-06-15
true
false
Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO
0
Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO
🤝
CombinHorizon/YiSM-blossom5.1-34B-SLERP
31.09
50.33
0.5
46.4
0.62
19.79
0.2
14.09
0.36
14.37
0.44
41.56
0.47
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
apache-2.0
34
0
true
ebd8d6507623008567a0548cd0ff9e28cbd6a656
true
true
2024-08-27
2024-08-27
true
false
CombinHorizon/YiSM-blossom5.1-34B-SLERP
1
CombinHorizon/YiSM-blossom5.1-34B-SLERP (Merge)
💬
CohereForAI/c4ai-command-r-plus
30.86
76.64
0.77
39.92
0.58
7.55
0.08
7.38
0.31
20.42
0.48
33.24
0.4
💬 chat models (RLHF, DPO, IFT, ...)
CohereForCausalLM
Original
float16
true
cc-by-nc-4.0
103
1,652
true
fa1bd7fb1572ceb861bbbbecfa8af83b29fa8cca
true
true
2024-06-13
2024-04-03
true
true
CohereForAI/c4ai-command-r-plus
0
CohereForAI/c4ai-command-r-plus
💬
mattshumer/ref_70_e3
30.74
62.94
0.63
49.27
0.65
0
0
11.41
0.34
13
0.43
47.81
0.53
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
float16
true
llama3.1
70
46
true
5d2d9dbb9e0bf61879255f63f1b787296fe524cc
true
true
2024-09-08
2024-09-08
true
false
mattshumer/ref_70_e3
2
meta-llama/Meta-Llama-3.1-70B
💬
internlm/internlm2_5-7b-chat
30.46
61.4
0.61
57.67
0.71
8.31
0.08
10.63
0.33
14.35
0.44
30.42
0.37
💬 chat models (RLHF, DPO, IFT, ...)
InternLM2ForCausalLM
Original
float16
true
other
7
154
true
bebb00121ee105b823647c3ba2b1e152652edc33
true
true
2024-07-03
2024-06-27
true
true
internlm/internlm2_5-7b-chat
0
internlm/internlm2_5-7b-chat
💬
ValiantLabs/Llama3-70B-ShiningValiant2
30.45
61.22
0.61
46.71
0.63
7.1
0.07
10.74
0.33
13.64
0.43
43.31
0.49
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3
70
4
true
bd6cce8da08ccefe9ec58cae3df4bf75c97d8950
true
true
2024-07-25
2024-04-20
true
false
ValiantLabs/Llama3-70B-ShiningValiant2
0
ValiantLabs/Llama3-70B-ShiningValiant2
🤝
altomek/YiSM-34B-0rn
30.15
42.84
0.43
45.38
0.61
20.62
0.21
16.22
0.37
14.76
0.44
41.06
0.47
🤝 base merges and moerges
LlamaForCausalLM
Original
float16
false
apache-2.0
34
1
true
7a481c67cbdd5c846d6aaab5ef9f1eebfad812c2
true
true
2024-06-27
2024-05-26
true
false
altomek/YiSM-34B-0rn
1
altomek/YiSM-34B-0rn (Merge)
💬
OpenBuddy/openbuddy-yi1.5-34b-v21.3-32k
30.08
54.2
0.54
45.64
0.62
12.76
0.13
13.2
0.35
14.69
0.44
39.99
0.46
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
34
0
true
966be6ad502cdd50a9af94d5f003aec040cdb0b5
true
false
2024-08-30
2024-06-05
true
false
OpenBuddy/openbuddy-yi1.5-34b-v21.3-32k
0
OpenBuddy/openbuddy-yi1.5-34b-v21.3-32k
🤝
paloalma/ECE-TW3-JRGL-V1
30.02
55.35
0.55
46.7
0.63
11.86
0.12
12.98
0.35
17.46
0.46
35.79
0.42
🤝 base merges and moerges
LlamaForCausalLM
Original
float16
false
apache-2.0
68
1
true
2f08c7ab9db03b1b9f455c7beee6a41e99aa910e
true
true
2024-08-04
2024-04-03
false
false
paloalma/ECE-TW3-JRGL-V1
0
paloalma/ECE-TW3-JRGL-V1
🔶
failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5
29.97
77.47
0.77
37.87
0.57
11.86
0.12
6.26
0.3
7.97
0.4
38.36
0.45
🔶 fine-tuned on domain-specific datasets
?
Adapter
bfloat16
true
llama3
70
33
true
fc951b03d92972ab52ad9392e620eba6173526b9
true
true
2024-08-30
2024-05-28
true
false
failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5
0
failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5
💬
recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
29.87
76.49
0.76
42.25
0.6
1.74
0.02
10.74
0.33
12.39
0.42
35.63
0.42
💬 chat models (RLHF, DPO, IFT, ...)
Gemma2ForCausalLM
Original
float16
false
apache-2.0
10
2
true
9048af8616bc62b6efab2bc1bc77ba53c5dfed79
true
true
2024-09-12
2024-09-11
true
false
recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
1
recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp (Merge)
🔶
jpacifico/Chocolatine-14B-Instruct-4k-DPO
29.83
46.89
0.47
48.02
0.63
14.88
0.15
12.19
0.34
15.15
0.44
41.82
0.48
🔶 fine-tuned on domain-specific datasets
Phi3ForCausalLM
Original
float16
true
mit
13
1
true
30677e58010979af26b70240846fdf7ff38cbbf2
true
true
2024-08-08
2024-08-01
false
false
jpacifico/Chocolatine-14B-Instruct-4k-DPO
0
jpacifico/Chocolatine-14B-Instruct-4k-DPO
💬
microsoft/Phi-3-small-8k-instruct
29.64
64.97
0.65
46.21
0.62
2.64
0.03
8.28
0.31
16.77
0.46
38.96
0.45
💬 chat models (RLHF, DPO, IFT, ...)
Phi3SmallForCausalLM
Original
bfloat16
true
mit
7
150
true
1535ae26fb4faada95c6950e8bc6e867cdad6b00
true
true
2024-06-13
2024-05-07
true
true
microsoft/Phi-3-small-8k-instruct
0
microsoft/Phi-3-small-8k-instruct
💬
Qwen/Qwen2-57B-A14B-Instruct
29.6
63.38
0.63
41.79
0.59
7.7
0.08
10.85
0.33
14.18
0.44
39.73
0.46
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2MoeForCausalLM
Original
bfloat16
true
apache-2.0
57
74
true
5ea455a449e61a92a5b194ee06be807647d3e8b5
true
true
2024-08-14
2024-06-04
true
true
Qwen/Qwen2-57B-A14B-Instruct
1
Qwen/Qwen2-57B-A14B
🟢
Qwen/Qwen1.5-110B
29.56
34.22
0.34
44.28
0.61
23.04
0.23
13.65
0.35
13.71
0.44
48.45
0.54
🟢 pretrained
Qwen2ForCausalLM
Original
bfloat16
true
other
111
90
true
16659038ecdcc771c1293cf47020fa7cc2750ee8
true
true
2024-06-13
2024-04-25
false
true
Qwen/Qwen1.5-110B
0
Qwen/Qwen1.5-110B
💬
anthracite-org/magnum-v3-34b
29.39
51.15
0.51
44.33
0.61
17.82
0.18
14.77
0.36
6.57
0.39
41.69
0.48
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
null
34
26
false
3bcd8c3dbb93021a5ce22203c690a1a084cafb73
true
true
2024-09-05
2024-08-22
true
false
anthracite-org/magnum-v3-34b
0
anthracite-org/magnum-v3-34b
🔶
abacusai/Smaug-72B-v0.1
29.35
51.67
0.52
43.13
0.6
16.77
0.17
9.84
0.32
14.42
0.45
40.26
0.46
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
other
72
463
true
a1d657156f82c24b670158406378648233487011
true
true
2024-06-12
2024-02-02
false
true
abacusai/Smaug-72B-v0.1
1
moreh/MoMo-72B-lora-1.8.7-DPO
💬
Qwen/Qwen1.5-110B-Chat
29.22
59.39
0.59
44.98
0.62
0
0
12.19
0.34
16.29
0.45
42.5
0.48
💬 chat models (RLHF, DPO, IFT, ...)
Qwen2ForCausalLM
Original
bfloat16
true
other
111
122
true
85f86cec25901f2dbd870a86e06756903c9a876a
true
true
2024-06-12
2024-04-25
true
true
Qwen/Qwen1.5-110B-Chat
0
Qwen/Qwen1.5-110B-Chat
🤝
paloalma/ECE-TW3-JRGL-V5
29.19
45.53
0.46
43.46
0.6
16.54
0.17
12.19
0.34
16.89
0.46
40.53
0.46
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
apache-2.0
72
0
true
4061fa10de22945790cad825f7f4dec96d55b204
true
true
2024-08-30
2024-04-11
false
false
paloalma/ECE-TW3-JRGL-V5
0
paloalma/ECE-TW3-JRGL-V5
🤝
DreadPoor/Heart_Stolen-8B-Model_Stock
28.98
72.45
0.72
34.44
0.54
14.65
0.15
8.95
0.32
12.36
0.42
31.04
0.38
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
apache-2.0
8
2
true
6d77987af7115c7455ddb072c48316815b018999
true
true
2024-09-10
2024-09-09
true
false
DreadPoor/Heart_Stolen-8B-Model_Stock
1
DreadPoor/Heart_Stolen-8B-Model_Stock (Merge)
🤝
Dampfinchen/Llama-3.1-8B-Ultra-Instruct
28.98
80.81
0.81
32.49
0.53
14.95
0.15
5.59
0.29
8.61
0.4
31.4
0.38
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
llama3
8
5
true
46662d14130cfd34f7d90816540794f24a301f86
true
true
2024-08-26
2024-08-26
true
false
Dampfinchen/Llama-3.1-8B-Ultra-Instruct
1
Dampfinchen/Llama-3.1-8B-Ultra-Instruct (Merge)
💬
01-ai/Yi-1.5-34B-Chat-16K
28.98
45.64
0.46
44.54
0.61
18.81
0.19
11.74
0.34
13.74
0.44
39.38
0.45
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
34
27
true
ff74452e11f0f749ab872dc19b1dd3813c25c4d8
true
true
2024-07-15
2024-05-15
true
true
01-ai/Yi-1.5-34B-Chat-16K
0
01-ai/Yi-1.5-34B-Chat-16K
💬
google/gemma-2-9b-it
28.86
74.36
0.74
42.14
0.6
0.23
0
14.77
0.36
9.74
0.41
31.95
0.39
💬 chat models (RLHF, DPO, IFT, ...)
Gemma2ForCausalLM
Original
bfloat16
true
gemma
9
453
true
1937c70277fcc5f7fb0fc772fc5bc69378996e71
true
true
2024-07-11
2024-06-24
true
true
google/gemma-2-9b-it
1
google/gemma-2-9b
🔶
152334H/miqu-1-70b-sf
28.82
51.82
0.52
43.81
0.61
10.8
0.11
13.42
0.35
17.21
0.46
35.87
0.42
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
null
68
218
false
1dca4cce36f01f2104ee2e6b97bac6ff7bb300c1
true
true
2024-06-26
2024-01-30
false
false
152334H/miqu-1-70b-sf
0
152334H/miqu-1-70b-sf
🔶
ehristoforu/Gemma2-9b-it-train6
28.75
70.25
0.7
40.99
0.59
8.38
0.08
10.51
0.33
9.65
0.41
32.69
0.39
🔶 fine-tuned on domain-specific datasets
Gemma2ForCausalLM
Original
float16
true
apache-2.0
9
1
true
e72bf00b427c22c48b468818cf75300a373a0c8a
true
true
2024-07-31
2024-07-22
true
false
ehristoforu/Gemma2-9b-it-train6
6
unsloth/gemma-2-9b-it-bnb-4bit
💬
microsoft/Phi-3-small-128k-instruct
28.59
63.68
0.64
45.63
0.62
0
0
8.95
0.32
14.5
0.44
38.78
0.45
💬 chat models (RLHF, DPO, IFT, ...)
Phi3SmallForCausalLM
Original
bfloat16
true
mit
7
165
true
f80aaa30bfc64c2b8ab214b541d9050e97163bc4
true
true
2024-06-13
2024-05-07
true
true
microsoft/Phi-3-small-128k-instruct
0
microsoft/Phi-3-small-128k-instruct
🔶
VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct
28.56
80.17
0.8
31
0.51
11.18
0.11
5.37
0.29
11.52
0.41
32.12
0.39
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
8
25
true
23ca79966a4ab0a61f7ccc7a0454ffef553b66eb
true
true
2024-07-29
2024-07-25
true
false
VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct
0
VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct
🔶
abhishek/autotrain-llama3-70b-orpo-v2
28.48
54.06
0.54
39.88
0.59
18.73
0.19
5.82
0.29
9.95
0.41
42.42
0.48
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
other
70
2
true
a2c16a8a7fa48792eb8a1f0c50e13309c2021a63
true
true
2024-08-21
2024-05-04
true
false
abhishek/autotrain-llama3-70b-orpo-v2
0
abhishek/autotrain-llama3-70b-orpo-v2
💬
Azure99/blossom-v5.1-34b
28.39
56.97
0.57
44.15
0.61
14.43
0.14
7.94
0.31
7.3
0.39
39.53
0.46
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
34
5
true
2c803204f5dbf4ce37e2df98eb0205cdc53de10d
true
true
2024-07-27
2024-05-19
true
false
Azure99/blossom-v5.1-34b
0
Azure99/blossom-v5.1-34b
🟢
dnhkng/RYS-Phi-3-medium-4k-instruct
28.38
43.91
0.44
46.75
0.62
11.78
0.12
13.98
0.35
11.09
0.43
42.74
0.48
🟢 pretrained
Phi3ForCausalLM
Original
bfloat16
true
mit
17
1
true
1009e916b1ff8c9a53bc9d8ff48bea2a15ccde26
true
true
2024-08-07
2024-08-06
false
false
dnhkng/RYS-Phi-3-medium-4k-instruct
0
dnhkng/RYS-Phi-3-medium-4k-instruct
🤝
DeepAutoAI/ldm_soup_Llama-3.1-8B-Instruct-v0.1
28.28
78.89
0.79
31.16
0.51
10.42
0.1
5.48
0.29
11.52
0.41
32.17
0.39
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
true
null
8
0
false
ecd140c95985b4292c896e25a94a7629d2924ad1
true
true
2024-09-16
2024-09-15
true
false
DeepAutoAI/ldm_soup_Llama-3.1-8B-Instruct-v0.1
0
DeepAutoAI/ldm_soup_Llama-3.1-8B-Instruct-v0.1
🤝
DeepAutoAI/ldm_soup_Llama-3.1-8B-Instruct-v0.0
28.28
78.89
0.79
31.16
0.51
10.42
0.1
5.48
0.29
11.52
0.41
32.17
0.39
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
true
null
8
0
false
210a97b4dadbda63cc9fe459e8415d4cd3bbaf99
true
true
2024-09-15
2024-09-14
true
false
DeepAutoAI/ldm_soup_Llama-3.1-8B-Instruct-v0.0
0
DeepAutoAI/ldm_soup_Llama-3.1-8B-Instruct-v0.0
🤝
bunnycore/HyperLlama-3.1-8B
28.07
78.83
0.79
29.81
0.51
16.01
0.16
4.92
0.29
7.93
0.38
30.92
0.38
🤝 base merges and moerges
LlamaForCausalLM
Original
bfloat16
false
apache-2.0
8
3
true
659b18ffaee2c1e8dbe8a9a56a44502325d71696
true
true
2024-09-05
2024-09-04
true
false
bunnycore/HyperLlama-3.1-8B
0
bunnycore/HyperLlama-3.1-8B
🔶
NLPark/AnFeng_v3.1-Avocet
28.05
50.96
0.51
40.31
0.58
13.9
0.14
9.96
0.32
14.98
0.45
38.2
0.44
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
float16
true
cc-by-nc-nd-4.0
34
0
true
5170739731033323e6e66a0f68d34790042a3b2a
true
true
2024-08-07
2024-08-03
false
false
NLPark/AnFeng_v3.1-Avocet
0
NLPark/AnFeng_v3.1-Avocet
🤝
OpenBuddy/openbuddy-zero-56b-v21.2-32k
27.99
50.57
0.51
44.8
0.61
12.99
0.13
9.06
0.32
12.78
0.43
37.77
0.44
🤝 base merges and moerges
LlamaForCausalLM
Original
float16
true
other
56
0
true
c7a1a4a6e798f75d1d3219ab9ff9f2692e29f7d5
true
true
2024-06-26
2024-06-10
true
false
OpenBuddy/openbuddy-zero-56b-v21.2-32k
0
OpenBuddy/openbuddy-zero-56b-v21.2-32k
🔶
Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
27.93
77.92
0.78
29.69
0.51
16.92
0.17
4.36
0.28
7.77
0.38
30.9
0.38
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
llama3.1
8
29
true
2340f8fbcd2452125a798686ca90b882a08fb0d9
true
true
2024-08-28
2024-08-09
true
false
Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
0
Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
💬
meta-llama/Meta-Llama-3.1-8B-Instruct
27.91
78.56
0.79
29.89
0.51
17.6
0.18
2.35
0.27
8.41
0.39
30.68
0.38
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
llama3.1
8
2,447
true
df34336b42332c6d360959e259cd6271c6a09fd4
true
true
2024-08-15
2024-07-18
true
true
meta-llama/Meta-Llama-3.1-8B-Instruct
1
meta-llama/Meta-Llama-3.1-8B
💬
vicgalle/Configurable-Llama-3.1-8B-Instruct
27.77
83.12
0.83
29.66
0.5
15.86
0.16
3.24
0.27
5.93
0.38
28.8
0.36
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
float16
true
apache-2.0
8
10
true
133b3ab1a5385ff9b3d17da2addfe3fc1fd6f733
true
true
2024-08-05
2024-07-24
true
false
vicgalle/Configurable-Llama-3.1-8B-Instruct
0
vicgalle/Configurable-Llama-3.1-8B-Instruct
🔶
BAAI/Infinity-Instruct-3M-0625-Yi-1.5-9B
27.74
51.86
0.52
35.38
0.55
13.97
0.14
13.87
0.35
16.72
0.46
34.65
0.41
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
8
3
true
a42c86c61b98ca4fdf238d688fe6ea11cf414d29
true
true
2024-08-05
2024-07-09
true
false
BAAI/Infinity-Instruct-3M-0625-Yi-1.5-9B
0
BAAI/Infinity-Instruct-3M-0625-Yi-1.5-9B
🔶
cognitivecomputations/dolphin-2.9.1-yi-1.5-34b
27.73
38.53
0.39
44.17
0.61
15.18
0.15
12.42
0.34
16.97
0.46
39.1
0.45
🔶 fine-tuned on domain-specific datasets
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
34
34
true
1ec522298a6935c881df6dc29d3669833bd8672d
true
true
2024-07-27
2024-05-18
true
true
cognitivecomputations/dolphin-2.9.1-yi-1.5-34b
1
01-ai/Yi-1.5-34B
💬
01-ai/Yi-1.5-9B-Chat
27.71
60.46
0.6
36.95
0.56
11.63
0.12
11.3
0.33
12.84
0.43
33.06
0.4
💬 chat models (RLHF, DPO, IFT, ...)
LlamaForCausalLM
Original
bfloat16
true
apache-2.0
8
128
true
bc87d8557c98dc1e5fdef6ec23ed31088c4d3f35
true
true
2024-06-12
2024-05-10
true
true
01-ai/Yi-1.5-9B-Chat
0
01-ai/Yi-1.5-9B-Chat
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