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Dapinsky/PIT-4B-FT-202212-math-reasoning-sft

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Dapinsky/PIT-4B-FT-202212-math-reasoning-sft

This repo contains a full merged model produced from Diamegs/PIT-4B-FT-202212 and a PEFT LoRA adapter. It is intended to be loadable with the same Transformers API used for the base Diamegs PIT model:

python

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("Dapinsky/PIT-4B-FT-202212-math-reasoning-sft", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Dapinsky/PIT-4B-FT-202212-math-reasoning-sft", trust_remote_code=True)

Training Summary

—Base model: Diamegs/PIT-4B-FT-202212
—Fine-tuning method: supervised fine-tuning with LoRA, merged into the base weights for upload.
—Tokenizer files copied from: base model

LoRA Configuration

json

{
  "peft_type": "LORA",
  "task_type": "CAUSAL_LM",
  "r": 16,
  "lora_alpha": 32,
  "lora_dropout": 0.05,
  "target_modules": [
    "c_proj",
    "c_q",
    "c_k",
    "c_fc",
    "c_v"
  ],
  "base_model_name_or_path": "Diamegs/PIT-4B-FT-202212"
}