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Model: NightPrince/Qwen3-4B-Islamic-Arabic Source: Original Platform
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README.md
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---
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language:
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- ar
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license: apache-2.0
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library_name: transformers
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base_model: Qwen/Qwen3-4B
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datasets:
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- NightPrince/islamic-arabic-qa
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tags:
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- arabic
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- islamic
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- fiqh
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- fatwa
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- qlora
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- peft
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- qwen3
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- instruction-tuning
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- conversational
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pipeline_tag: text-generation
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inference:
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parameters:
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max_new_tokens: 512
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temperature: 0.3
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do_sample: true
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widget:
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- text: "ما حكم زكاة الفطر وما مقدارها؟"
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example_title: "زكاة الفطر"
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- text: "ما الفرق بين الفرض والواجب عند الحنفية؟"
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example_title: "الفرض والواجب"
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- text: "ما حكم بيع العينة في الفقه الإسلامي؟"
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example_title: "بيع العينة"
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- text: "ما شروط صحة الصلاة؟"
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example_title: "شروط الصلاة"
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model-index:
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- name: Qwen3-4B-Islamic-Arabic
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Islamic Arabic Q&A
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type: NightPrince/islamic-arabic-qa
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split: validation
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metrics:
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- name: Validation Loss
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type: loss
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value: 2.4094
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verified: false
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---
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# Qwen3-4B-Islamic-Arabic
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**Qwen3-4B fine-tuned on Islamic Arabic Q&A via QLoRA — merged FP16, ready for direct inference.**
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This is the canonical, fully merged version of a Qwen3-4B model fine-tuned on 17,944 high-quality Islamic Arabic question-answer pairs spanning Fiqh, Fatwa, Aqeedah, Quran Sciences, and Islamic Finance. The LoRA adapter has been merged into the base weights and saved in FP16; no additional adapter loading is required.
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Trained by **[Yahya Alnwsany (NightPrince)](https://huggingface.co/NightPrince)** — 2026-05-05.
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---
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## Model Variants
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| Variant | Repo | Description |
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|---|---|---|
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| **Merged FP16** (this model) | [NightPrince/Qwen3-4B-Islamic-Arabic](https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic) | Canonical merged model, FP16, ~7.6 GB — drop-in for transformers or vLLM |
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| **LoRA Adapter** | [NightPrince/Qwen3-4B-Islamic-Arabic-LoRA](https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic-LoRA) | PEFT adapter only, 264 MB — apply on top of `Qwen/Qwen3-4B` |
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| **INT4 Quantized** | [NightPrince/Qwen3-4B-Islamic-Arabic-INT4](https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic-INT4) | W4A16 compressed-tensors for fast vLLM serving, 2.5 GB |
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| **MLX 4-bit** | [NightPrince/Qwen3-4B-Islamic-Arabic-mlx-4Bit](https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic-mlx-4Bit) | Apple Silicon / MLX — native Mac inference, 4-bit quantized |
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| **GGUF** | [NightPrince/Qwen3-4B-Islamic-Arabic-GGUF](https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic-GGUF) | llama.cpp / Ollama / LM Studio — Q4_K_M (2.3 GB), Q8_0 (4.0 GB), F16 (7.5 GB) |
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| **Dataset** | [NightPrince/islamic-arabic-qa](https://huggingface.co/datasets/NightPrince/islamic-arabic-qa) | 17,944 train / 2,101 val / 1,042 test — Islamic Arabic Q&A pairs |
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---
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## Training Metrics
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### Loss Curve
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| Checkpoint | Train Loss | Eval Loss |
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|---|---|---|
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| Step 0 (init) | — | — |
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| Step 843 (final) | **1.8918** | **2.4094** (best) |
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### Token Accuracy
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| Phase | Token Accuracy |
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|---|---|
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| Early training | ~50% |
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| End of training | ~60% |
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> **MCQ evaluation coming soon** — a multiple-choice benchmark (Islamics domain) is prepared but requires serving the model via vLLM. Results will be posted here once available.
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---
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## Usage
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### Transformers Inference
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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model_id = "NightPrince/Qwen3-4B-Islamic-Arabic"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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SYSTEM_PROMPT = (
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"أنت مساعد عالم إسلامي متخصص. "
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"أجب على الأسئلة بدقة استناداً إلى القرآن الكريم والسنة النبوية والفقه الإسلامي الكلاسيكي. "
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"استشهد بالمصادر حيثما أمكن. كن موجزاً لكن شاملاً."
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)
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messages = [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": "ما حكم الزكاة على المال المدخر؟"},
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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inputs = tokenizer(text, return_tensors="pt").to(model.device)
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=512,
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temperature=0.7,
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top_p=0.9,
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do_sample=True,
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)
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response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
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print(response)
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```
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### vLLM Serving
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The merged FP16 model is ~7.6 GB. Use at least `tensor_parallel_size=2` on 11 GB GPUs (e.g., RTX 2080 Ti), or a single 24 GB+ GPU.
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```bash
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# Install vLLM if needed
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pip install vllm
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# Serve with tensor parallelism across 2 GPUs
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vllm serve NightPrince/Qwen3-4B-Islamic-Arabic \
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--dtype float16 \
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--tensor-parallel-size 2 \
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--max-model-len 4096 \
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--port 8000
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```
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Query the running server:
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```python
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from openai import OpenAI
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client = OpenAI(base_url="http://localhost:8000/v1", api_key="token-abc123")
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SYSTEM_PROMPT = (
|
||||
"أنت مساعد عالم إسلامي متخصص. "
|
||||
"أجب على الأسئلة بدقة استناداً إلى القرآن الكريم والسنة النبوية والفقه الإسلامي الكلاسيكي. "
|
||||
"استشهد بالمصادر حيثما أمكن. كن موجزاً لكن شاملاً."
|
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)
|
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|
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response = client.chat.completions.create(
|
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model="NightPrince/Qwen3-4B-Islamic-Arabic",
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messages=[
|
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{"role": "system", "content": SYSTEM_PROMPT},
|
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{"role": "user", "content": "ما حكم الزكاة على المال المدخر؟"},
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],
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max_tokens=512,
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temperature=0.7,
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)
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print(response.choices[0].message.content)
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```
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> **Prefer lower memory?** Use the [INT4 quantized variant](https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic-INT4) (2.5 GB) for vLLM or the [GGUF variant](https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic-GGUF) for llama.cpp / Ollama.
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|
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---
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## Training Details
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||||
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### Dataset
|
||||
|
||||
| Property | Value |
|
||||
|---|---|
|
||||
| Dataset | [NightPrince/islamic-arabic-qa](https://huggingface.co/datasets/NightPrince/islamic-arabic-qa) |
|
||||
| Train split | 17,944 samples |
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| Validation split | 2,101 samples |
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| Test split | 1,042 samples |
|
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| Language | Arabic (Modern Standard + Classical) |
|
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| Domains | Fiqh, Fatwa, Aqeedah, Quran Sciences, Islamic Finance |
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| Quality filter | Applied — deduplication, length filtering, domain relevance scoring |
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| Format | Instruction-following (system / user / assistant) |
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### Hyperparameters
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| Hyperparameter | Value |
|
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|---|---|
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| Epochs | 3 |
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| Per-device batch size | 1 |
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| Gradient accumulation steps | 16 |
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| Effective batch size | 64 |
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| Learning rate | 2e-4 |
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| LR scheduler | Cosine with warmup |
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| Warmup ratio | 0.05 |
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| Max sequence length | 1,024 tokens |
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| Optimizer | AdamW (paged, 8-bit) |
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| Precision | QLoRA (4-bit base + BF16 adapters) |
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| Gradient checkpointing | Enabled |
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| Loss masking | Assistant turns only (`assistant_only_loss=True`) |
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### LoRA Configuration
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| Parameter | Value |
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|---|---|
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| Rank (r) | 64 |
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| Alpha (α) | 128 |
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| Dropout | 0.05 |
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| Target modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
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| Trainable parameters | 132,120,576 |
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| % of total parameters | 5.65% of 4.15B |
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### Results
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| Metric | Value |
|
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|---|---|
|
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| Final train loss | 1.8918 |
|
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| Best eval loss | 2.4094 |
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| Total training steps | 843 |
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| Training duration | 7.59 hours |
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| Token accuracy (start → end) | ~50% → ~60% |
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| MCQ benchmark | Coming soon (requires vLLM serving) |
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### Hardware
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| Component | Specification |
|
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|---|---|
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| GPUs | 4× NVIDIA GeForce RTX 2080 Ti (11 GB VRAM each, 44 GB total) |
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| CUDA version | 13.0 |
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| Training framework | DDP via Hugging Face Accelerate |
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### Software Environment
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| Library | Version |
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|---|---|
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| Python | 3.11.15 |
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| PyTorch | 2.11.0+cu130 |
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| Transformers | 4.57.6 |
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| PEFT | 0.18.1 |
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| TRL | 1.3.0 |
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| BitsAndBytes | 0.49.2 |
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| Accelerate | 1.13.0 |
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---
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## Limitations
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- **Domain scope**: The model is optimized for Islamic Arabic Q&A. General Arabic tasks or non-Islamic domains may show degraded quality compared to the base Qwen3-4B.
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- **Source attribution**: While the model is trained to cite sources, citations should be independently verified — the model can produce plausible-sounding but incorrect references.
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- **Classical vs. contemporary Fiqh**: The training data emphasizes classical scholarship. Contemporary jurisprudential debates, especially minority or regional opinions, may be underrepresented.
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- **Language**: The model performs best in Arabic (Modern Standard and Classical). Responses in other languages are not guaranteed to be accurate or fluent.
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---
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## Citation
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```bibtex
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@misc{alnwsany2026qwen3islamicarbic,
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author = {Yahya Alnwsany},
|
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title = {Qwen3-4B-Islamic-Arabic: QLoRA Fine-Tuning of Qwen3-4B on Islamic Arabic Q\&A},
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year = {2026},
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howpublished = {\url{https://huggingface.co/NightPrince/Qwen3-4B-Islamic-Arabic}},
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note = {Base model: Qwen/Qwen3-4B. Dataset: NightPrince/islamic-arabic-qa.}
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}
|
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```
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---
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## License
|
||||
|
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This model is released under the **Apache 2.0** license, consistent with the base model [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B). See [LICENSE](https://www.apache.org/licenses/LICENSE-2.0) for details.
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28
added_tokens.json
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
|
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"<|vision_start|>": 151652
|
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}
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89
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
|
||||
{{- '<|im_start|>system\n' }}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- messages[0].content + '\n\n' }}
|
||||
{%- endif %}
|
||||
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
|
||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||
{%- for message in messages[::-1] %}
|
||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
||||
{%- set ns.multi_step_tool = false %}
|
||||
{%- set ns.last_query_index = index %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- for message in messages %}
|
||||
{%- if message.content is string %}
|
||||
{%- set content = message.content %}
|
||||
{%- else %}
|
||||
{%- set content = '' %}
|
||||
{%- endif %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is string %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in content %}
|
||||
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- if loop.index0 > ns.last_query_index %}
|
||||
{%- if loop.last or (not loop.last and reasoning_content) %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- if enable_thinking is defined and enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
68
config.json
Normal file
68
config.json
Normal file
@@ -0,0 +1,68 @@
|
||||
{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"dtype": "float16",
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 9728,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 40960,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "4.57.6",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
13
generation_config.json
Normal file
13
generation_config.json
Normal file
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"temperature": 0.6,
|
||||
"top_k": 20,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "4.57.6"
|
||||
}
|
||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model-00001-of-00002.safetensors
Normal file
3
model-00001-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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oid sha256:9400026db84288a5337a11b0f6528d91c1d3b930d4c56bb188a6751146742611
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size 4967215128
|
||||
3
model-00002-of-00002.safetensors
Normal file
3
model-00002-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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size 3077766464
|
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406
model.safetensors.index.json
Normal file
406
model.safetensors.index.json
Normal file
@@ -0,0 +1,406 @@
|
||||
{
|
||||
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||||
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31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
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3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
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|
||||
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||||
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239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
||||
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|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user