Model Visualization

Hamanasu 15B Instruct

🌌 Overview

Thanks to PocketDoc's Adventure datasets and taking his Dangerous Winds models as inspiration, I was able to finetune a Adventure Version of Hamanasu Instruct This model remains non-sloppy and now support adventure-style cards such as my very own Dinosaur Adventure Card

⚔️ Hardware

  • 4x RTX 3090 GPUs
  • Epochs: 2
  • Base: Hamanasu-15B-Instruct

💰 Prompting

A known quirk of the model is overly verbose responses when generation length is uncapped, Please cap your maximum output tokens to 100~ tokens above what you prefer

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.

Axolotl Config ꒰(˶• ᴗ •˶)꒱

base_model: Delta-Vector_Hamanasu-15B-Instruct
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true


load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: PocketDoc/Dans-Personamaxx-VN
    type: dan-chat-advanced
  - path: NewEden/vanilla-backrooms-claude-sharegpt
    type: dan-chat-advanced
  - path: PocketDoc/Dans-Prosemaxx-Cowriter-3-S
    type: dan-chat-advanced
  - path: NewEden/Misc-Mang-Sharegpt
    type: dan-chat-advanced
  - path: PocketDoc/Dans-Prosemaxx-Adventure
    type: dan-chat-advanced    
  - path: PocketDoc/Dans-Failuremaxx-Adventure-3
    type: dan-chat-advanced  
  - path: PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot
    type: dan-chat-advanced  
  - path: PocketDoc/Dans-Prosemaxx-InstructWriter-Continue
    type: dan-chat-advanced  

shuffle_merged_datasets: true
dataset_prepared_path: prepared_data
val_set_size: 0.0
output_dir: ./phi4-adventure

sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true

adapter: lora
lora_model_dir:
lora_r: 128
lora_alpha: 16 
lora_dropout: 0.05
lora_target_modules:
  - gate_proj
  - down_proj
  - up_proj
  - q_proj
  - v_proj
  - k_proj
  - o_proj

lora_modules_to_save:
 - embed_tokens
 - lm_head


wandb_project: mag-phi
wandb_entity:
wandb_watch:
wandb_name: adventure-attempt-01
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 2
optimizer: paged_ademamix_8bit
lr_scheduler: cosine
learning_rate: 2e-5

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: 15
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 2
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.01
fsdp:
fsdp_config:

⚡ Credits


Made by
Delta-Vector
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