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README.md

@@ -1,3 +1,7 @@
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 # 🚀 OpenAI GPT OSS Models - Simple Generation Script
 
 Generate synthetic datasets using OpenAI's GPT OSS models with transparent reasoning. Works on HuggingFace Jobs with L4 GPUs!
@@ -21,26 +25,28 @@ hf jobs uv run --flavor l4x4 --secrets HF_TOKEN=hf_*** \
 
 ## 📋 Script Options
 
-| Option | Description | Default |
-|--------|-------------|---------|
-| `--input-dataset` | HuggingFace dataset to process | Required |
-| `--output-dataset` | Output dataset name | Required |
-| `--prompt-column` | Column containing prompts | `prompt` |
-| `--model-id` | Model to use | `openai/gpt-oss-20b` |
-| `--max-samples` | Limit samples to process | None (all) |
-| `--max-new-tokens` | Max tokens to generate | Auto-scales: 512/1024/2048 |
-| `--reasoning-effort` | Reasoning depth: low/medium/high | `medium` |
-| `--temperature` | Sampling temperature | `1.0` |
-| `--top-p` | Top-p sampling | `1.0` |
+| Option               | Description                      | Default                    |
+| -------------------- | -------------------------------- | -------------------------- |
+| `--input-dataset`    | HuggingFace dataset to process   | Required                   |
+| `--output-dataset`   | Output dataset name              | Required                   |
+| `--prompt-column`    | Column containing prompts        | `prompt`                   |
+| `--model-id`         | Model to use                     | `openai/gpt-oss-20b`       |
+| `--max-samples`      | Limit samples to process         | None (all)                 |
+| `--max-new-tokens`   | Max tokens to generate           | Auto-scales: 512/1024/2048 |
+| `--reasoning-effort` | Reasoning depth: low/medium/high | `medium`                   |
+| `--temperature`      | Sampling temperature             | `1.0`                      |
+| `--top-p`            | Top-p sampling                   | `1.0`                      |
 
 **Note**: `max-new-tokens` auto-scales based on `reasoning-effort` if not set:
+
 - `low`: 512 tokens
-- `medium`: 1024 tokens  
+- `medium`: 1024 tokens
 - `high`: 2048 tokens (prevents truncation of detailed reasoning)
 
 ## 💡 What You Get
 
 The output dataset contains:
+
 - `prompt`: Original prompt from input dataset
 - `raw_output`: Full model response with channel markers
 - `model`: Model ID used
@@ -49,10 +55,12 @@ The output dataset contains:
 ### Understanding the Output
 
 The raw output contains special channel markers:
+
 - `<|channel|>analysis<|message|>` - Chain of thought reasoning
 - `<|channel|>final<|message|>` - The actual response
 
 Example raw output structure:
+
 ```
 <|channel|>analysis<|message|>
 [Reasoning about the task...]
@@ -65,6 +73,7 @@ Example raw output structure:
 ### Test with Different Reasoning Levels
 
 **High reasoning (most detailed):**
+
 ```bash
 hf jobs uv run --flavor l4x4 --secrets HF_TOKEN=hf_*** \
     https://huggingface.co/datasets/davanstrien/openai-oss/raw/main/gpt_oss_minimal.py \
@@ -76,6 +85,7 @@ hf jobs uv run --flavor l4x4 --secrets HF_TOKEN=hf_*** \
 ```
 
 **Low reasoning (fastest):**
+
 ```bash
 hf jobs uv run --flavor l4x4 --secrets HF_TOKEN=hf_*** \
     https://huggingface.co/datasets/davanstrien/openai-oss/raw/main/gpt_oss_minimal.py \
@@ -88,29 +98,34 @@ hf jobs uv run --flavor l4x4 --secrets HF_TOKEN=hf_*** \
 
 ## 🖥️ GPU Requirements
 
-| Model | Memory Required | Recommended Flavor |
-|-------|----------------|-------------------|
-| **openai/gpt-oss-20b** | ~40GB | `l4x4` (4x24GB = 96GB) |
-| **openai/gpt-oss-120b** | ~240GB | `8xa100` (8x80GB) |
+| Model                   | Memory Required | Recommended Flavor     |
+| ----------------------- | --------------- | ---------------------- |
+| **openai/gpt-oss-20b**  | ~40GB           | `l4x4` (4x24GB = 96GB) |
+| **openai/gpt-oss-120b** | ~240GB          | `8xa100` (8x80GB)      |
 
 **Note**: The 20B model automatically dequantizes from MXFP4 to bf16 on non-Hopper GPUs, requiring more memory than the quantized size.
 
 ## 🔧 Technical Details
 
 ### Why L4x4?
+
 - The 20B model needs ~40GB VRAM when dequantized
 - Single A10G (24GB) is insufficient
 - L4x4 provides 96GB total memory across 4 GPUs
 - Cost-effective compared to A100 instances
 
 ### Reasoning Effort
+
 The `reasoning_effort` parameter controls how much chain-of-thought reasoning the model generates:
+
 - `low`: Quick responses with minimal reasoning
 - `medium`: Balanced reasoning (default)
 - `high`: Detailed step-by-step reasoning
 
 ### Sampling Parameters
+
 OpenAI recommends `temperature=1.0` and `top_p=1.0` as defaults for GPT OSS models:
+
 - These settings provide good diversity without compromising quality
 - The model was trained to work well with these parameters
 - Adjust only if you need specific behavior (e.g., lower temperature for more deterministic output)
@@ -123,4 +138,4 @@ OpenAI recommends `temperature=1.0` and `top_p=1.0` as defaults for GPT OSS mode
 
 ---
 
-*Last tested: 2025-01-06 on HF Jobs with l4x4 flavor*
+_Last tested: 2025-01-06 on HF Jobs with l4x4 flavor_