--- license: other license_name: mrl language: - en tags: - chat pipeline_tag: text-generation library_name: transformers --- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a46cbfb9c2bdfae75b3a6/PeLc_rlHB98Hw4eojizIi.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 [mistralai/Mistral-Large-Instruct-2407](https://huggingface.co/mistralai/Mistral-Large-Instruct-2407). ## Prompting A typical input would look like this: ```py [INST] SYSTEM MESSAGE\nUSER 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: mistralai/Mistral-Large-Instruct-2407 model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true liger_fused_linear_cross_entropy: true load_in_8bit: false load_in_4bit: false strict: false datasets: - path: anthracite-org/c2_logs_16k_mistral-large_v1.2 type: sharegpt conversation: mistral - path: anthracite-org/kalo-opus-instruct-22k-no-refusal type: sharegpt conversation: mistral - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered type: sharegpt conversation: mistral - path: anthracite-org/nopm_claude_writing_fixed type: sharegpt conversation: mistral - path: anthracite-org/kalo_opus_misc_240827 type: sharegpt conversation: mistral - path: anthracite-org/kalo_misc_part2 type: sharegpt conversation: mistral #chat_template: chatml shuffle_merged_datasets: true #default_system_message: "You are an assistant that responds to the user." dataset_prepared_path: ./data/magnum-123b-data val_set_size: 0.0 output_dir: ./data/123b-fft-out sequence_len: 16384 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: 123b-magnum-fft wandb_entity: wandb_watch: wandb_name: alter-attempt-04 wandb_log_model: gradient_accumulation_steps: 4 micro_batch_size: 1 num_epochs: 2 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.0000015 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: false gradient_checkpointing: unsloth 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: 0.01 fsdp: fsdp_config: special_tokens: ```

## Credits We'd like to thank [Eric Hartford](https://huggingface.co/ehartford) for sponsoring the compute for this train. We would also like to thank all members of Anthracite who made this finetune possible. ## Datasets - [anthracite-org/c2_logs_16k_mistral-large_v1.2](https://huggingface.co/datasets/anthracite-org/c2_logs_16k_mistral-large_v1.2) - [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal) - [lodrick-the-lafted/kalo-opus-instruct-3k-filtered](https://huggingface.co/datasets/lodrick-the-lafted/kalo-opus-instruct-3k-filtered) - [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed) - [anthracite-org/kalo_opus_misc_240827](https://huggingface.co/datasets/anthracite-org/kalo_opus_misc_240827) - [anthracite-org/kalo_misc_part2](https://huggingface.co/datasets/anthracite-org/kalo_misc_part2) ## Training We used 8x mi300x GPUs graciously provided by [Eric Hartford](https://huggingface.co/ehartford) for the full-parameter fine-tuning of the model. [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) ## Safety ...