Uploaded model

  • Developed by: Ka3456
  • License: apache-2.0
  • Finetuned from model : llm-jp/llm-jp-3-13b

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.


from transformers import (
    AutoModelForCausalLM,
    AutoTokenizer,
    BitsAndBytesConfig,
)
import torch
import json
from tqdm import tqdm

# Hugging FaceのトークンとモデルID
HF_TOKEN = "your-token"  # Hugging Faceトークンを記入
model_id = "Ka3456/practice5_lora"  # 新しいモデルID

# LoRAモデルのロード
bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.bfloat16,
    bnb_4bit_use_double_quant=False,
)

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    trust_remote_code=True,
    quantization_config=bnb_config,
    use_auth_token=HF_TOKEN,
)

tokenizer = AutoTokenizer.from_pretrained(
    model_id,
    trust_remote_code=True,
    use_auth_token=HF_TOKEN,
)

# データセットの読み込み
datasets = []
with open("elyza-tasks-100-TV_0.jsonl", "r") as f:
    item = ""
    for line in f:
        line = line.strip()
        item += line
        if item.endswith("}"):
            datasets.append(json.loads(item))
            item = ""

# モデル推論
results = []
for dt in tqdm(datasets):
    input_text = dt["input"]
    prompt = f"### 指示\n{input_text}\n### 回答\n"

    inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
    outputs = model.generate(
        **inputs,
        max_new_tokens=512,
        use_cache=True,
        do_sample=False,
        repetition_penalty=1.2,
    )

    prediction = tokenizer.decode(outputs[0], skip_special_tokens=True).split("\n### 回答")[-1]
    results.append({"task_id": dt["task_id"], "input": input_text, "output": prediction})

# 推論結果を保存
output_file = f"{model_id}_output.jsonl"
with open(output_file, "w", encoding="utf-8") as f:
    for result in results:
        json.dump(result, f, ensure_ascii=False)
        f.write("\n")

print(f"推論結果を {output_file} に保存しました。")

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no pipeline_tag.

Model tree for Ka3456/practice5_lora

Finetuned
(1120)
this model