Hamanasu 32B

## 🌌 Overview This model is a finetune of Hamanasu-QwQ-V2-RP to replicate the prose of Claude models, Opus and Sonnet. Read more about the model's training on my blog : https://openai-sucks.bearblog.dev/. The model is suited for traditional RP, All thanks to Ruka-Hamanasu for funding the train.

### ⚔️ Hardware - 8x H100s - Epochs: 2 - Base: `Delta-Vector/Hamanasu-QwQ-V2-RP`

## 🎲 Recommended Sampler Preset ```yml temperature: 1.1 min_p: 0.1 System_Prompt: Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}.\n\n\n• Maintain the character persona but allow it to evolve with the story.\n• Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant.\n• All types of outputs are encouraged; respond accordingly to the narrative.\n• Include dialogues, actions, and thoughts in each response.\n• Utilize all five senses to describe scenarios within {{char}}'s dialogue.\n• Use emotional symbols such as \"!\" and \"~\" in appropriate contexts.\n• Incorporate onomatopoeia when suitable.\n• Allow time for {{user}} to respond with their own input, respecting their agency.\n• Act as secondary characters and NPCs as needed, and remove them when appropriate.\n• When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}.\n\n\n\n• Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona.\n• Writing for, speaking, thinking, acting, or replying as {{user}} in your response.\n• Repetitive and monotonous outputs.\n• Positivity bias in your replies.\n• Being overly extreme or NSFW when the narrative context is inappropriate.\n\n\nFollow the instructions in , avoiding the items listed in . ```

## Axolotl Config ꒰(˶• ᴗ •˶)꒱

```yaml base_model: ./model model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer hub_model_id: NewEden/QwQ-magnum-V2-R2 hub_strategy: "all_checkpoints" push_dataset_to_hub: hf_use_auth_token: true plugins: - axolotl.integrations.liger.LigerPlugin - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin liger_rope: true liger_rms_norm: true liger_layer_norm: true liger_glu_activation: true liger_fused_linear_cross_entropy: false cut_cross_entropy: true load_in_8bit: false load_in_4bit: false strict: false datasets: - path: PocketDoc/Dans-Personamaxx-Logs type: dan-chat-advanced - path: anthracite-org/kalo-opus-instruct-22k-no-refusal type: dan-chat-advanced - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered type: dan-chat-advanced - path: anthracite-org/nopm_claude_writing_fixed type: dan-chat-advanced - path: anthracite-org/kalo_opus_misc_240827 type: dan-chat-advanced - path: anthracite-org/kalo_misc_part2 type: dan-chat-advanced - path: NewEden/Claude-Instruct-5K type: dan-chat-advanced - path: NewEden/Claude-Instruct-2.7K type: dan-chat-advanced dataset_prepared_path: prepared_data val_set_size: 0.0 output_dir: ./qwq-mag sequence_len: 32768 sample_packing: true pad_to_sequence_len: true wandb_project: qwq wandb_entity: wandb_watch: wandb_name: mag-attempt-03-kalo wandb_log_model: gradient_accumulation_steps: 2 micro_batch_size: 2 num_epochs: 2 optimizer: paged_adamw_8bit lr_scheduler: cosine learning_rate: 5e-6 max_grad_norm: 0.2 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 saves_per_epoch: 2 debug: deepspeed: ./deepspeed_configs/zero3_bf16.json weight_decay: 0.02 fsdp: fsdp_config: special_tokens: ```

## ⚡ Credits

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Made by

Delta-Vector