README.md

---
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
---


![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.