ArmandS11/DeepSeekR1-7B-FineTuned-python

DeepSeek-R1-Distill-Qwen-7B — Python Code Fine-tune

A LoRA fine-tuned version of DeepSeek-R1-Distill-Qwen-7B specialized for Python code generation.

Model Details

Model Description

• Developed by: Armand (@ArmanS11)
• Model type: Large Language Model — LoRA fine-tune
• Language(s): English
• License: MIT
• Finetuned from: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B

Model Sources

• Base model: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
• Training dataset: https://huggingface.co/datasets/iamtarun/python_code_instructions_18k_alpaca

Uses

Direct Use

Generate Python code from natural language instructions. Examples:

• Writing functions, classes, algorithms
• Async/await patterns
• Data structures and error handling

Out-of-Scope Use

• Not intended for other programming languages
• Not suitable for production security-critical code without review

Bias, Risks, and Limitations

Generated code should always be reviewed before use in production. The model may occasionally produce syntactically incorrect code, particularly for complex async patterns.

Training Details

Training Data

iamtarun/python_code_instructions_18k_alpaca — 18,612 Python code instruction/response pairs.

• Train split: 17,681 examples
• Validation split: 931 examples

Training Hyperparameters

Parameter	Value
Method	LoRA
LoRA Rank	8
LoRA Layers	8
Learning Rate	5e-6
Batch Size	2
Iterations	2000
Quantization	4-bit

Technical Specifications

Compute Infrastructure

Hardware

• Apple MacBook Pro M4 — 16 GB unified memory

Software

• MLX (Apple Silicon optimized)
• M-Courtyard fine-tuning app

Model Card Authors

Armand — @ArmandS11