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---
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**書きなさい。"
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)