File size: 1,386 Bytes
aa90ed5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | ---
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
|