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Delta-Vector/Hamanasu-4B-Chat-Brainrot
Hamanasu-4B-Chat-Brainrot is a machine learning model from Delta-Vector. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Downloads · 30 days
21
7% of all-time downloads
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From the Hugging Face model README
<i>This model is the Chat tune of the Instruct model, More accurately it is the "brainrotted" version, Finetuned with Bsky, 4chan and Discord logs, Its... really something beautiful. </i>
<i>The model is suited best towards being a highly dumb chat partner rather then regular RP</i>
<i>The model is suited for traditional RP, All thanks to Tav for funding the train.</i>
<i>Support me and my finetunes on Ko-Fi https://ko-fi.com/deltavector</i>
</div> <div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 20px; margin: 20px 0;"> <div style="border:2px solid #333; border-radius:10px; padding:20px; background: rgba(0,0,0,0.2);">Delta-Vector/Hamanasu-4B-Instruct-KTO-V2<i>This model uses ChatML formatting</i>
<|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.
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ST sampler preset: https://files.catbox.moe/wtkp0l.json
System prompt: Blank.
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ase_model: ./model
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
hub_model_id: NewEden/Hamanasu-4B-RP-v2
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true
## qlora COPE
load_in_8bit: false
load_in_4bit: false
strict: false
## data
datasets:
- path: NewEden/Discord-Filtered
type: dan-chat-advanced
- path: NewEden/Basket-Weaving-Filtered
type: dan-chat-advanced
- path: NewEden/Misc-Data-Sharegpt-Prefixed
type: dan-chat-advanced
- path: NewEden/BlueSky-10K-Complexity
type: dan-chat-advanced
- path: PocketDoc/Dans-Kinomaxx-VanillaBackrooms
type: dan-chat-advanced
- path: PocketDoc/Dans-Personamaxx-VN
type: dan-chat-advanced
- path: NewEden/LIMARP-Complexity
type: dan-chat-advanced
- path: NewEden/OpenCAI-ShareGPT
type: dan-chat-advanced
- path: NewEden/Creative_Writing-Complexity
type: dan-chat-advanced
- path: NewEden/DeepseekRP-Filtered
type: dan-chat-advanced
- path: NewEden/Storium-Prefixed-Clean
type: dan-chat-advanced
shuffle_merged_datasets: true
dataset_prepared_path: dataset_prepared-2
val_set_size: 0.01
output_dir: 4b-out
## LIGGER
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
## CTX settings
sequence_len: 32768
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
## Lora
#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_fan_in_fan_out:
#peft_use_rslora: true
#lora_modules_to_save:
# - embed_tokens
# - lm_head
## WandB
wandb_project: tavbussy
wandb_entity:
wandb_watch:
wandb_name: chat-v2
wandb_log_model:
## evals
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
## hoe params
gradient_accumulation_steps: 2
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 2e-5
max_grad_norm: 0.2
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:
warmup_steps: 40
saves_per_epoch: 2
debug:
deepspeed: ./deepspeed_configs/zero3_bf16.json
weight_decay: 0.02
fsdp:
fsdp_config:
special_tokens:
pad_token: <|finetune_right_pad_id|>
</details>
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