--- language: - en license: other library_name: transformers tags: - chat license_name: mrl pipeline_tag: text-generation model-index: - name: magnum-v4-22b results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 56.29 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 35.55 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 17.6 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 10.4 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 13.43 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 31.44 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-22b name: Open LLM Leaderboard --- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a46cbfb9c2bdfae75b3a6/WvQykcYiK13x7sMI93T6e.png) This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of [Mistral-Small-Instruct-2409](https://huggingface.co/mistralai/Mistral-Small-Instruct-2409). ## Prompting A typical input would look like this: ```py [INST] SYSTEM MESSAGE USER MESSAGE[/INST] ASSISTANT MESSAGE[INST] USER MESSAGE[/INST] ``` ## SillyTavern templates Below are Instruct and Context templates for use within SillyTavern.
context template ```yaml default SillyTavern template works fine ```

instruct template ```yaml default SillyTavern template works fine ```

## Axolotl config
See axolotl config ```yaml base_model: /workspace/models/Mistral-Small-Instruct-2409 model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer hub_model_id: anthracite-org/magnum-v4-22b-r4 hub_strategy: "all_checkpoints" push_dataset_to_hub: hf_use_auth_token: true plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true #liger_cross_entropy: true liger_fused_linear_cross_entropy: true load_in_8bit: false load_in_4bit: false strict: false datasets: - path: anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system type: custommistralv2v3 - path: anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system type: custommistralv2v3 - path: anthracite-org/kalo-opus-instruct-3k-filtered-no-system type: custommistralv2v3 - path: anthracite-org/nopm_claude_writing_fixed type: custommistralv2v3 - path: anthracite-org/kalo_opus_misc_240827_no_system type: custommistralv2v3 - path: anthracite-org/kalo_misc_part2_no_system type: custommistralv2v3 #chat_template: mistral_v2v3 shuffle_merged_datasets: true #default_system_message: "You are an assistant that responds to the user." dataset_prepared_path: /workspace/data/magnum-22b-data val_set_size: 0.0 output_dir: /workspace/data/22b-r4-fft-out sequence_len: 32768 sample_packing: true pad_to_sequence_len: true adapter: lora_model_dir: lora_r: lora_alpha: lora_dropout: lora_target_linear: lora_fan_in_fan_out: wandb_project: 22b-magnum-fft wandb_entity: wandb_watch: wandb_name: v4-r4-attempt-01 wandb_log_model: gradient_accumulation_steps: 2 micro_batch_size: 1 num_epochs: 2 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.000004 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: false gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 40 evals_per_epoch: eval_table_size: eval_max_new_tokens: saves_per_epoch: 2 debug: deepspeed: deepspeed_configs/zero3_bf16.json weight_decay: 0.1 fsdp: fsdp_config: special_tokens: ```

## Credits We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow. We would also like to thank all members of Anthracite who made this finetune possible. ## Datasets - [anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system](https://huggingface.co/datasets/anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system) - [anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system) - [anthracite-org/kalo-opus-instruct-3k-filtered-no-system](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-3k-filtered-no-system) - [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed) - [anthracite-org/kalo_opus_misc_240827_no_system](https://huggingface.co/datasets/anthracite-org/kalo_opus_misc_240827_no_system) - [anthracite-org/kalo_misc_part2_no_system](https://huggingface.co/datasets/anthracite-org/kalo_misc_part2_no_system) ## Training The training was done for 2 epochs. We used 8x[H100s](https://www.nvidia.com/en-us/data-center/h100/) GPUs graciously provided by [Recursal AI](https://recursal.ai/) / [Featherless AI](https://featherless.ai/) for the full-parameter fine-tuning of the model. [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) ## Safety ... # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_anthracite-org__magnum-v4-22b) | Metric |Value| |-------------------|----:| |Avg. |27.45| |IFEval (0-Shot) |56.29| |BBH (3-Shot) |35.55| |MATH Lvl 5 (4-Shot)|17.60| |GPQA (0-shot) |10.40| |MuSR (0-shot) |13.43| |MMLU-PRO (5-shot) |31.44|