AraCode-7B-LoRA

LoRA adapter weights for AraCode-7B — the first open-source Arabic-specialized code explanation model.

This adapter can be loaded on top of the base model for Arabic code explanation, generation, and discussion.

Benchmarks

Benchmark	Score
Arabic Code Explanation	100% (5/5)
MBPP Syntax Rate	92.3%
MBPP Execution Rate	82.3%
Multi-Language (Python / JS / SQL)	3/3
Inference Speed	25.9 tok/s

Usage

from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="rahimdzx/AraCode-7B-LoRA",
    max_seq_length=2048,
    load_in_4bit=True,
)
FastLanguageModel.for_inference(model)

prompt = "اشرح الكود التالي بالعربية:\ndef fibonacci(n):\n    if n <= 1: return n\n    return fibonacci(n-1) + fibonacci(n-2)"

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=300)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Available Formats

Format	Repo	Size	Use Case
GGUF Q4_K_M	AraCode-7B-GGUF	4.68 GB	Local inference, Ollama, llama.cpp
LoRA Adapter	AraCode-7B-LoRA	162 MB	Fine-tuning, research, Unsloth

Links

• GGUF Version: rahimdzx/AraCode-7B-GGUF

License

Apache 2.0