Add model card

README.md

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+---
+license: mit
+language:
+- en
+tags:
+- code-generation
+- codefeedback
+- hrm-text
+base_model: sapientai/HRM-Text-1B
+---
+
+# HRM-Text-1B-Code-Feedback
+
+Fine-tuned version of [HRM-Text-1B](https://huggingface.co/sapientai/HRM-Text-1B) on the CodeFeedback dataset for code generation.
+
+## Model Details
+
+- **Base Model:** sapientai/HRM-Text-1B (1B parameters, hierarchical reasoning model)
+- **Training Data:** CodeFeedback dataset (~131k samples, filtered to <= 4096 tokens)
+- **Training:** 2 epochs, ~8 hours on L40S GPU
+- **Architecture:** Hierarchical Reasoning Model with H_cycles=2, L_cycles=3
+
+## Training Data Distribution
+
+| Language | Samples |
+|----------|---------|
+| Python | ~80k |
+| JavaScript | ~7.6k |
+| React | ~550 |
+
+## Performance
+
+| Task | Base | Fine-tuned |
+|------|------|------------|
+| C++ factorial | Broken (repeating includes) | Correct |
+| JS reverse | Wrong syntax | Correct syntax |
+| Java max | Wrong type | Better structure |
+
+## Usage
+
+
+
+## Training Details
+
+- **Framework:** PyTorch with FlashAttention 3
+- **Loss:** Cross-entropy
+- **Hardware:** AWS L40S GPU
+- **Training Time:** ~8 hours
+
+## Limitations
+
+- Maximum sequence length: 4096 tokens
+- Requires FlashAttention 3 for inference (Ada Lovelace or newer GPUs)
+- Limited React/TypeScript performance due to small training data
+- Best performance on Python code generation
+
+## License
+
+MIT License