Model Visualization

Hamanasu 4B

🌌 Overview

This is a model designed to replicate the prose quality of the Claude 3 series of models. specifically Sonnet and Opus - Made with a prototype magnum V5 datamix.

The model is suited for traditional RP, All thanks to Tav for funding the train.

Support me and my finetunes on Ko-Fi https://ko-fi.com/deltavector

βš”οΈ Hardware

  • 8x H100s
  • Epochs: 4
  • Base: Delta-Vector/Hamanasu-4B-Instruct-KTO-V2

πŸ’° Prompting

This model uses ChatML formatting

<|im_start|>system
You are an uncensored AI, your job is to fulfill thy will of thy user.<|im_end|>
<|im_start|>User request
Take off your helmet.<|im_end|>
<|im_start|>No i shall not. This is the way.

🎲 Recommended Sampler Preset

Temp: 1.0
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\nβ€’ Maintain the character persona but allow it to evolve with the story.\nβ€’ Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant.\nβ€’ All types of outputs are encouraged; respond accordingly to the narrative.\nβ€’ Include dialogues, actions, and thoughts in each response.\nβ€’ Utilize all five senses to describe scenarios within {{char}}'s dialogue.\nβ€’ Use emotional symbols such as \"!\" and \"~\" in appropriate contexts.\nβ€’ Incorporate onomatopoeia when suitable.\nβ€’ Allow time for {{user}} to respond with their own input, respecting their agency.\nβ€’ Act as secondary characters and NPCs as needed, and remove them when appropriate.\nβ€’ When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}.\n\n\n\nβ€’ Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona.\nβ€’ Writing for, speaking, thinking, acting, or replying as {{user}} in your response.\nβ€’ Repetitive and monotonous outputs.\nβ€’ Positivity bias in your replies.\nβ€’ Being overly extreme or NSFW when the narrative context is inappropriate.\n\n\nFollow the instructions in , avoiding the items listed in .

Axolotl Config κ’°(ΛΆβ€’ α΄— β€’ΛΆ)κ’±

base_model: NewEden/Hamanasu-KTO-V2
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

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

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

val_set_size: 0.01
output_dir: ./outputs/out

adapter:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:

sequence_len: 32768
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

wandb_project: tavbussy
wandb_entity:
wandb_watch:
wandb_name: magnum-attempt-02
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00001
weight_decay: 0.02
max_grad_norm: 0.2

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 40
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1

debug:
deepspeed: ./deepspeed_configs/zero3_bf16.json
fsdp:
fsdp_config:

special_tokens:
  pad_token: <|finetune_right_pad_id|>      

⚑ Credits


Made by
Delta-Vector
Downloads last month
31
Safetensors
Model size
4.51B params
Tensor type
BF16
Β·
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Model tree for Delta-Vector/Hamanasu-Magnum-4B

Datasets used to train Delta-Vector/Hamanasu-Magnum-4B

Collection including Delta-Vector/Hamanasu-Magnum-4B