DeepSeek React Reviewer
A fine-tuned DeepSeek-Coder model focused on reviewing React and JavaScript code, identifying issues, and suggesting best practices.
This model is optimized to act as a code reviewer, not just a code generator.
Base Model
- DeepSeek-Coder (
deepseek-ai/deepseek-coder) - Architecture: Causal Language Model
Fine-Tuning
- Method: LoRA (Low-Rank Adaptation)
- Framework: Unsloth + Transformers
- Training: Supervised fine-tuning (SFT)
- Precision: FP16 (LoRA merged)
- Training quantization: 4-bit (QLoRA-style)
The model uploaded here is fully merged, so it can be used directly for inference without PEFT dependencies.
Training Data
- Format: Chat-style JSONL
- Focus areas:
- React code review
- JavaScript / JSX patterns
- Hooks misuse
- Common bugs and anti-patterns
- Performance and best practices
⚠️ The dataset may contain synthetic or curated examples and should not be treated as authoritative.
Intended Use
Recommended for:
- Reviewing React and JavaScript code
- Explaining bugs and anti-patterns
- Suggesting improvements and best practices
- Educational feedback for frontend developers
Not intended for:
- Security audits
- Production-critical code review
- Executing untrusted code
Author
Fine-tuned by Nabin Raj Pandey
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