---
library_name: transformers
datasets:
- elyza/ELYZA-tasks-100
license: apache-2.0
language:
- ja
base_model:
- llm-jp/llm-jp-3-13b-instruct
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->

## Required Libraries and Their Versions

- trl==0.12.2
- transformers<4.47.0
- tokenizers==0.21.0

## Usage

```py
results = []
system_text = "以下は、タスクを説明する指示です。要求を適切に満たす回答を**簡潔に**書いてください。回答の後ろに、回答の理由を**1文で**書いてください。"
for data in tqdm(datasets):

  input_text = data["input"]

  prompt = f"""
  {system_text}
  ### 指示
  {input_text}
  ### 応答
  """

  tokenized_input = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt").to(model.device)
  attention_mask = torch.ones_like(tokenized_input)

  with torch.no_grad():
      outputs = model.generate(
          tokenized_input,
          attention_mask=attention_mask,
          max_new_tokens=100,
          do_sample=False,
          repetition_penalty=1.2,
          pad_token_id=tokenizer.eos_token_id
      )[0]
  output = tokenizer.decode(outputs[tokenized_input.size(1):], skip_special_tokens=True)

  results.append({"task_id": data["task_id"], "input": input_text, "output": output})

```


## Model Details

- **Model type:** Transformer-based Language Model

## Datasets

### Instruction tuning

| Language | Dataset | description |
|:---|:---|:---|
|Japanese|[elyza/ELYZA-tasks-100](https://huggingface.co/datasets/elyza/ELYZA-tasks-100)| A manually constructed instruction dataset |

## License

[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)