Downloads · 30 days
0
AraCode-7B-LoRA
rahimdzx/AraCode-7B-LoRA
AraCode-7B-LoRA is a machine learning model from rahimdzx. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
LoRA adapter weights for AraCode-7B — the first open-source Arabic-specialized code explanation model.
Access
Public
Updated Apr 5, 2026
Repo size
173 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors162 MB · 93%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Apr 4, 2026
- Updated
- Apr 5, 2026
- SHA
- 1667e69c
Model card
From the Hugging Face model README
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
- License
- apache-2.0
- Languages
- ar, en
- Created
- Apr 4, 2026
- Updated
- Apr 5, 2026