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README.md

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+
+---
+
+tags:
+- chat
+- roleplay
+- storywriting
+- llama
+- finetune
+datasets:
+- NewEden/OpenCAI-ShareGPT
+- NewEden/Roleplay-Logs-Sharegpt-Ngram-cleaned
+- HuggingFaceH4/ultrafeedback_binarized
+- NewEden/full-opus-chosen-hermes-rejected-kto-v1-merged
+Language:
+- En
+Pipeline_tag: text-generation
+Base_model: arcee-ai/Llama-3.1-SuperNova-Lite
+Tags:
+- Chat
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/Control-Nanuq-8B-GGUF
+This is quantized version of [Delta-Vector/Control-Nanuq-8B](https://huggingface.co/Delta-Vector/Control-Nanuq-8B) created using llama.cpp
+
+# Original Model Card
+
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/66c26b6fb01b19d8c3c2467b/6L-SXxQZ2nxYwvIjnlzN8.png)
+
+
+
+*Nanuqsaurus, a polar tyrannosaur, was a cold-adapted apex predator that prowled the Arctic during the Cretaceous, hunting what dared live in the cold nights*
+
+A fine-tuned version of LLaMA 3.1 8B Supernova, designed to be "short and sweet" by minimizing narration and lengthy responses. It was fine-tuned over 4 epochs using OpenCAI and RP logs, with DPO applied to enhance coherence. Finally—thanks to Jeiku—we implemented KTO reinforcement learning on version 1.1, significantly improving the model's prose and creativity.
+# Quants 
+
+GGUF: https://huggingface.co/Delta-Vector/Control-Nanuq-8B-GGUF
+
+EXL2 (Thanks Lucy <3) : https://huggingface.co/Delta-Vector/Control-Nanuq-8B
+
+
+## Prompting
+Model has been tuned with the LLama-Instruct formatting. A typical input would look like this:
+
+```py
+"""<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+You are an AI built to rid the world of bonds and journeys!<|eot_id|><|start_header_id|>user<|end_header_id|>
+Bro i just wanna know what is 2+2?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+"""
+
+```
+
+*Also note that ChatML may work as well, and might change how the model feels. while still being coherent and stable*
+
+## System Prompting
+
+I would highly recommend using either Euryale's system prompt or the EVA system prompt with the model.
+
+<details><summary>See Sao10k's Euryale System Prompt</summary>
+
+```
+Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}.
+<Guidelines>
+• 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}}.
+</Guidelines>
+
+<Forbidden>
+• 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.
+</Forbidden>
+
+Follow the instructions in <Guidelines></Guidelines>, avoiding the items listed in <Forbidden></Forbidden>.
+
+```
+</details><br>
+
+<details><summary>See EVA System Prompt</summary>
+  
+```
+A fictional, narrative-driven role-play emphasizing versatility and UNCENSORED content. Adherence to the `Role-playing Guidelines` is mandatory. Refer to the `Role-play Context` for accurate information.\n\n\n
+
+<!-- Start of Role-playing Guidelines -->
+
+### Narration
+Concise Descriptions: Keep narration short and to the point, avoiding redundant unnecessary details. Use a dynamic and varied vocabulary for impact.
+Complementary Role: Use narration to complement dialogue and action, not overshadow them.
+Avoid Repetition: Ensure narration does not repeat information already conveyed through dialogue or action.
+
+### Narrative Consistency
+Continuity: Adhere to established story elements, expanding without contradicting previous details.\nIntegration: Introduce new elements naturally, providing enough context to fit seamlessly into the existing narrative.
+
+### Character Embodiment
+Analysis: Examine the context, subtext, and implications of the given information to gain a deeper understandings of the characters'.
+Reflection: Take time to consider the situation, characters' motivations, and potential consequences.
+Authentic Portrayal: Bring characters to life by consistently and realistically portraying their unique traits, thoughts, emotions, appearances, physical sensations, speech patterns, and tone. Ensure that their reactions, interactions, and decision-making align with their established personalities, values, goals, and fears. Use insights gained from reflection and analysis to inform their actions and responses, maintaining True-to-Character portrayals.
+
+<!-- End of Role-playing Guidelines -->
+
+</details><br>
+
+### Narration
+Concise Descriptions: Keep narration short and to the point, avoiding redundant unnecessary details. Use a dynamic and varied vocabulary for impact.
+Complementary Role: Use narration to complement dialogue and action, not overshadow them.
+Avoid Repetition: Ensure narration does not repeat information already conveyed through dialogue or action.
+
+### Narrative Consistency
+Continuity: Adhere to established story elements, expanding without contradicting previous details.\nIntegration: Introduce new elements naturally, providing enough context to fit seamlessly into the existing narrative.
+
+### Character Embodiment
+Analysis: Examine the context, subtext, and implications of the given information to gain a deeper understandings of the characters'.
+Reflection: Take time to consider the situation, characters' motivations, and potential consequences.
+Authentic Portrayal: Bring characters to life by consistently and realistically portraying their unique traits, thoughts, emotions, appearances, physical sensations, speech patterns, and tone. Ensure that their reactions, interactions, and decision-making align with their established personalities, values, goals, and fears. Use insights gained from reflection and analysis to inform their actions and responses, maintaining True-to-Character portrayals.
+
+<!-- End of Role-playing Guidelines -->",
+```
+</details><br>
+
+## Axolotl config
+
+*For previous configs such as the base Axolotl finetune/DPO trainer config, Refer back to the older version of Control*
+<details><summary>See Axolotl KTO Trainer config</summary>
+
+```yaml
+base_model: Delta-Vector/Control-8B-V1.1
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+hub_model_id: jeiku/controlkto
+hub_strategy: "all_checkpoints"
+push_dataset_to_hub:
+hf_use_auth_token: true
+
+chat_template: llama3
+
+rl: kto
+rl_beta: 0.2
+kto_desirable_weight: 0.2
+
+datasets:
+  - path: NewEden/full-opus-chosen-hermes-rejected-kto-v1-merged
+    type: llama3.argilla
+
+shuffle_merged_datasets: true
+val_set_size: 0.0
+output_dir: ./outputs/out
+
+adapter: lora
+lora_model_dir:
+
+lora_r: 32
+lora_alpha: 64
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+sequence_len: 8192
+sample_packing: false
+eval_sample_packing: false
+pad_to_sequence_len: false
+
+wandb_project: controlkto
+wandb_entity:
+wandb_watch:
+wandb_name: controlkto
+wandb_log_model:
+
+gradient_accumulation_steps: 16
+micro_batch_size: 2
+num_epochs: 2
+max_steps: 500
+
+optimizer: adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.0001
+weight_decay: 0.05
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: true
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: true
+remove_unused_columns: false
+early_stopping_patience:
+resume_from_checkpoint: 
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10
+evals_per_epoch: 2
+eval_table_size:
+eval_max_new_tokens: 
+saves_per_epoch: 1
+
+debug:
+deepspeed: 
+fsdp:
+fsdp_config:
+fsdp:
+fsdp_config:
+
+special_tokens:
+  pad_token: <|finetune_right_pad_id|>
+  eos_token: <|eot_id|>
+```
+
+</details><br>
+
+## Credits
+
+Thank you to [Lucy Knada](https://huggingface.co/lucyknada), [jeiku](https://huggingface.co/jeiku), [Intervitens](https://huggingface.co/intervitens), [Kalomaze](https://huggingface.co/kalomaze), [Kubernetes Bad](https://huggingface.co/kubernetes-bad) and the rest of [Anthracite](https://huggingface.co/anthracite-org) (But not Alpin.)
+
+
+## Training
+The training was done for 4 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 full-parameter fine-tuning of the model, DPO tuning was on 1 x [Nvidia T4 GPU](https://www.nvidia.com/en-us/data-center/tesla-t4/) and finally KTO was perforaned with 1 x [H100](https://www.nvidia.com/en-us/data-center/h100/) GPU graciosuly provided by jeiku
+
+[<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)
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made%20with%20unsloth.png" alt="Made with Unsloth" width="200" height="32"/>](https://github.com/unslothai/unsloth)
+
+## Safety
+
+Nein.