![image/png](https://cdn-uploads.huggingface.co/production/uploads/66c26b6fb01b19d8c3c2467b/EXbNn0z9o5TCc2RF6An66.png) A finetune ontop of the orginial Francois-PE model that incorporates KTO to increase coherency and prose. The model aims to have short and sweet prose. # Quants GGUF: https://huggingface.co/Delta-Vector/Francois-Huali-12B-gguf EXL2 : https://huggingface.co/Delta-Vector/Francois-Huali-12B-exl2 ## Prompting Model has been tuned with the ChatML formatting. A typical input would look like this: ```py """<|im_start|>user Hi there!<|im_end|> <|im_start|>assistant Nice to meet you!<|im_end|> <|im_start|>user Can I ask a question?<|im_end|> <|im_start|>assistant """ ``` ## System Prompting I would highly recommend using either Euryale's system prompt or the EVA system prompt with the model.

See Sao10k's Euryale System Prompt

``` Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}. • Maintain the character persona but allow it to evolve with the story. • Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant. • All types of outputs are encouraged; respond accordingly to the narrative. • Include dialogues, actions, and thoughts in each response. • Utilize all five senses to describe scenarios within {{char}}'s dialogue. • Use emotional symbols such as "!" and "~" in appropriate contexts. • Incorporate onomatopoeia when suitable. • Allow time for {{user}} to respond with their own input, respecting their agency. • Act as secondary characters and NPCs as needed, and remove them when appropriate. • When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}. • Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona. • Writing for, speaking, thinking, acting, or replying as {{user}} in your response. • Repetitive and monotonous outputs. • Positivity bias in your replies. • Being overly extreme or NSFW when the narrative context is inappropriate. Thanks to Po Follow the instructions in , avoiding the items listed in . ```

## Axolotl config

See axolotl config

Axolotl version: ` 0.5.0` ```yaml base_model: Delta-Vector_Francois-PE-12B load_in_8bit: false load_in_4bit: false strict: false rl: kto kto_undesirable_weight: 1.0 #datasets: # - ds_type: json # data_files: # - NewEden/Ohashi-accepted-Hermes-rejected # split: train # type: chatml.argilla datasets: - path: NewEden/Opus-accepted-hermes-rejected-shuffled split: train type: chatml.argilla dataset_prepared_path: last_run_prepared val_set_size: 0.0 output_dir: ./francois-PE-kto-r1 remove_unused_columns: false adapter: lora lora_model_dir: sequence_len: 8192 pad_to_sequence_len: false lora_r: 64 lora_alpha: 32 lora_dropout: 0.0 lora_target_linear: true lora_fan_in_fan_out: lora_target_modules: - gate_proj - down_proj - up_proj - q_proj - v_proj - k_proj - o_proj wandb_project: KTO-NeMo wandb_entity: wandb_watch: wandb_name: Ohashi-accepted-hermes-rejected-r1 wandb_log_model: gradient_accumulation_steps: 4 micro_batch_size: 2 num_epochs: 1 optimizer: paged_adamw_8bit lr_scheduler: constant_with_warmup learning_rate: 1e-6 max_grad_norm: 0.01 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: true gradient_checkpointing: unsloth early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 25 evals_per_epoch: 4 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 1 debug: deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json weight_decay: 0.0 fsdp: fsdp_config: ```

## Credits Thank you to [Lucy Knada](https://huggingface.co/lucyknada), [Intervitens](https://huggingface.co/intervitens),[Cgato](https://huggingface.co/cgato), [Kubernetes Bad](https://huggingface.co/kubernetes-bad) and the rest of [Anthracite](https://huggingface.co/anthracite-org) ## Training The training was done for 1 epochs We used 4 x [RTX 3090s](https://www.nvidia.com/en-us/geforce/graphics-cards/30-series/rtx-3090-3090ti/) GPUs graciously provided by [Intervitens](https://huggingface.co/intervitens) for the fine-tuning of the model. [

](https://github.com/OpenAccess-AI-Collective/axolotl) ## Safety ![image/png](https://cdn-uploads.huggingface.co/production/uploads/66c26b6fb01b19d8c3c2467b/bL0o_4bvbkmzAvK3W8gu2.png)