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--- |
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tags: |
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- chat |
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datasets: |
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- NewEden/OpenCAI-ShareGPT |
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- NewEden/vanilla-backrooms-claude-sharegpt |
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- anthracite-org/kalo_opus_misc_240827 |
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- anthracite-org/kalo_misc_part2 |
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- NewEden/RP-logs-V2-Experimental |
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- NewEden/BlueSky-Experimental-sharegpt |
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- NewEden/Misc-Mang-Sharegpt |
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- NewEden/Opus-accepted-hermes-rejected-shuffled |
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Language: |
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- En |
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Pipeline_tag: text-generation |
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Base_model: Delta-Vector/Francois-PE-12B |
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Tags: |
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- Chat |
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--- |
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### GGUF quants |
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--- |
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### check [here](https://huggingface.co/Delta-Vector/Francois-Huali-12B) for BF16 |
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--- |
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A finetune ontop of the original Francois-PE model that incorporates KTO to increase coherency and prose. The model aims to have short and sweet prose. |
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# Quants |
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GGUF: https://huggingface.co/Delta-Vector/Francois-Huali-12B-gguf |
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EXL2 : https://huggingface.co/Delta-Vector/Francois-Huali-12B-exl2 |
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## Prompting |
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Model has been tuned with the ChatML formatting. A typical input would look like this: |
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```py |
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"""<|im_start|>user |
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Hi there!<|im_end|> |
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<|im_start|>assistant |
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Nice to meet you!<|im_end|> |
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<|im_start|>user |
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Can I ask a question?<|im_end|> |
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<|im_start|>assistant |
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""" |
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``` |
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## System Prompting |
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I would highly recommend using either Euryale's system prompt or the EVA system prompt with the model. |
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<details><summary>See Sao10k's Euryale System Prompt</summary> |
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``` |
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Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}. |
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<Guidelines> |
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• Maintain the character persona but allow it to evolve with the story. |
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• Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant. |
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• All types of outputs are encouraged; respond accordingly to the narrative. |
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• Include dialogues, actions, and thoughts in each response. |
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• Utilize all five senses to describe scenarios within {{char}}'s dialogue. |
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• Use emotional symbols such as "!" and "~" in appropriate contexts. |
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• Incorporate onomatopoeia when suitable. |
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• Allow time for {{user}} to respond with their own input, respecting their agency. |
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• Act as secondary characters and NPCs as needed, and remove them when appropriate. |
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• When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}. |
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</Guidelines> |
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<Forbidden> |
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• Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona. |
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• Writing for, speaking, thinking, acting, or replying as {{user}} in your response. |
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• Repetitive and monotonous outputs. |
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• Positivity bias in your replies. |
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• Being overly extreme or NSFW when the narrative context is inappropriate. |
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</Forbidden>Thanks to Po |
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Follow the instructions in <Guidelines></Guidelines>, avoiding the items listed in <Forbidden></Forbidden>. |
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``` |
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</details><br> |
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### exl2 quant (measurement.json in main branch) |
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--- |
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### check revisions for quants |
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--- |
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## Axolotl config |
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<details><summary>See axolotl config</summary> |
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Axolotl version: ` 0.5.0` |
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```yaml |
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base_model: Delta-Vector_Francois-PE-12B |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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rl: kto |
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kto_undesirable_weight: 1.0 |
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#datasets: |
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# - ds_type: json |
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# data_files: |
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# - NewEden/Ohashi-accepted-Hermes-rejected |
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# split: train |
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# type: chatml.argilla |
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datasets: |
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- path: NewEden/Opus-accepted-hermes-rejected-shuffled |
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split: train |
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type: chatml.argilla |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.0 |
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output_dir: ./francois-PE-kto-r1 |
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remove_unused_columns: false |
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adapter: lora |
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lora_model_dir: |
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sequence_len: 8192 |
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pad_to_sequence_len: false |
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lora_r: 64 |
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lora_alpha: 32 |
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lora_dropout: 0.0 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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wandb_project: KTO-NeMo |
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wandb_entity: |
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wandb_watch: |
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wandb_name: Ohashi-accepted-hermes-rejected-r1 |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 1 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: constant_with_warmup |
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learning_rate: 1e-6 |
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max_grad_norm: 0.01 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: true |
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gradient_checkpointing: unsloth |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 25 |
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evals_per_epoch: 4 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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``` |
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</details><br> |
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## Credits |
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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) |
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## Training |
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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. |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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## Safety |
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