README.md

# 🚀 OpenAI GPT OSS Models - Open Source Language Models with Reasoning

Generate responses with transparent chain-of-thought reasoning using OpenAI's new open source GPT models. Run on cloud GPUs with zero setup!

## 🏁 Quick Setup for HF Jobs (One-time)

```bash
# Install huggingface-hub CLI using uv
uv tool install huggingface-hub

# Login to Hugging Face
huggingface-cli login

# Now you're ready to run jobs!
```

Need more help? Check the [HF Jobs documentation](https://huggingface.co/docs/huggingface_hub/guides/job).

## 🌟 Try It Now! Copy & Run This Command:

```bash
# Generate 50 haiku with reasoning (~5 minutes on A10G)
huggingface-cli job run --gpu-flavor a10g-small \
    uv run https://huggingface.co/datasets/uv-scripts/openai-oss/raw/main/gpt_oss_vllm.py \
    --input-dataset davanstrien/haiku_dpo \
    --output-dataset haiku-reasoning \
    --prompt-column question \
    --max-samples 50
```

That's it! Your dataset will be generated and pushed to `your-username/haiku-reasoning`. 🎉

## 💡 What You Get

The models output structured reasoning in separate channels:

```json
{
  "prompt": "Write a haiku about mountain serenity",
  "think": "I need to create a haiku with 5-7-5 syllable structure. Mountains suggest stillness, permanence. For serenity, I'll use calm imagery like 'silent peaks' (3 syllables)...",
  "content": "Silent peaks stand tall\nClouds drift through morning stillness\nPeace in stone and sky",
  "reasoning_level": "high",
  "model": "openai/gpt-oss-20b"
}
```

## 🎯 More Examples

### Use Your Own Dataset

```bash
# Process your entire dataset
huggingface-cli job run --gpu-flavor a10g-small \
    uv run https://huggingface.co/datasets/uv-scripts/openai-oss/raw/main/gpt_oss_vllm.py \
    --input-dataset your-prompts \
    --output-dataset my-responses

# Use the larger 120B model
huggingface-cli job run --gpu-flavor a100-large \
    uv run https://huggingface.co/datasets/uv-scripts/openai-oss/raw/main/gpt_oss_vllm.py \
    --input-dataset your-prompts \
    --output-dataset my-responses-120b \
    --model-id openai/gpt-oss-120b
```

### Process Different Dataset Types

```bash
# Math problems with step-by-step reasoning
huggingface-cli job run --gpu-flavor a10g-small \
    uv run https://huggingface.co/datasets/uv-scripts/openai-oss/raw/main/gpt_oss_vllm.py \
    --input-dataset math-problems \
    --output-dataset math-solutions \
    --reasoning-level high

# Code generation with explanation
huggingface-cli job run --gpu-flavor a10g-small \
    uv run https://huggingface.co/datasets/uv-scripts/openai-oss/raw/main/gpt_oss_vllm.py \
    --input-dataset code-prompts \
    --output-dataset code-explained \
    --max-tokens 1024

# Test with just 10 samples
huggingface-cli job run --gpu-flavor a10g-small \
    uv run https://huggingface.co/datasets/uv-scripts/openai-oss/raw/main/gpt_oss_vllm.py \
    --input-dataset your-dataset \
    --output-dataset quick-test \
    --max-samples 10
```

## 📦 Two Script Options

1. **`gpt_oss_vllm.py`** - High-performance batch generation using vLLM (recommended)
2. **`gpt_oss_transformers.py`** - Standard transformers implementation (fallback)

### Transformers Fallback (if vLLM has issues)

```bash
# Same command, different script!
huggingface-cli job run --gpu-flavor a10g-small \
    uv run https://huggingface.co/datasets/uv-scripts/openai-oss/raw/main/gpt_oss_transformers.py \
    --input-dataset davanstrien/haiku_dpo \
    --output-dataset haiku-reasoning \
    --prompt-column question \
    --max-samples 50
```

## 💰 GPU Flavors and Costs

| Model | GPU Flavor | Memory | Cost/Hour | Best For |
|-------|------------|--------|-----------|----------|
| `gpt-oss-20b` | `a10g-large` | 48GB | $2.50 | 20B model (needs ~40GB) |
| `gpt-oss-20b` | `a100-large` | 80GB | $4.34 | 20B with headroom |
| `gpt-oss-120b` | `4xa100` | 320GB | $17.36 | 120B model (needs ~240GB) |
| `gpt-oss-120b` | `8xl40s` | 384GB | $23.50 | 120B maximum speed |

**Note**: The MXFP4 quantization is dequantized to bf16 during loading, which doubles memory requirements.

## 🏃 Local Execution

If you have a local GPU:

```bash
# Using vLLM (recommended)
uv run gpt_oss_vllm.py \
    --input-dataset davanstrien/haiku_dpo \
    --output-dataset haiku-reasoning \
    --prompt-column question \
    --max-samples 50

# Using Transformers
uv run gpt_oss_transformers.py \
    --input-dataset davanstrien/haiku_dpo \
    --output-dataset haiku-reasoning \
    --prompt-column question \
    --max-samples 50
```

## 🛠️ Parameters

| Parameter | Description | Default |
|-----------|-------------|---------|
| `--input-dataset` | Source dataset on HF Hub | Required |
| `--output-dataset` | Output dataset name (auto-prefixed with your username) | Required |
| `--prompt-column` | Column containing prompts | `prompt` |
| `--model-id` | Model to use | `openai/gpt-oss-20b` |
| `--reasoning-level` | Reasoning depth (high/medium/low) | `high` |
| `--max-samples` | Limit number of examples | None (all) |
| `--temperature` | Generation temperature | `0.7` |
| `--max-tokens` | Max tokens to generate | `512` |

## 🎯 Key Features

- **Open Source Models**: `openai/gpt-oss-20b` and `openai/gpt-oss-120b`
- **Structured Output**: Separate channels for reasoning (`analysis`) and response (`final`)
- **Zero Setup**: Run with a single command on HF Jobs
- **Flexible Input**: Works with any prompt dataset
- **Automatic Upload**: Results pushed directly to your Hub account

## 🎯 Use Cases

1. **Training Data**: Create datasets with built-in reasoning explanations
2. **Evaluation**: Generate test sets where each answer includes its rationale
3. **Research**: Study how large models approach different types of problems
4. **Applications**: Build systems that can explain their outputs

## 🤔 Which Script to Use?

- **`gpt_oss_vllm.py`**: First choice for performance and scale
- **`gpt_oss_transformers.py`**: Fallback if vLLM has compatibility issues

## 🔧 Requirements

For HF Jobs:
- Hugging Face account (free)
- `huggingface-hub` CLI tool

For local execution:
- Python 3.10+
- GPU with CUDA support
- Hugging Face token

## 🤝 Contributing

This is part of the [uv-scripts](https://huggingface.co/uv-scripts) collection. Contributions and improvements welcome!

## 📜 License

Apache 2.0 - Same as the OpenAI GPT OSS models

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**Ready to generate data with reasoning?** Copy the command at the top and run it! 🚀