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---
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language:
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- ar
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- en
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base_model:
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- QCRI/Fanar-1-9B-Instruct
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pipeline_tag: text-generation
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---
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# Fanar-1-9B-Instruct — GGUF quantized
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This repo contains multiple **GGUF** builds of the Arabic-English LLM **Fanar-1-9B-Instruct**, the instruction-tuned variant of Fanar-1-9B created by QCRI / HBKU. The base model is a 9 B-parameter continuation of **gemma-2-9b** trained on ≈1 T Arabic + English tokens and aligned through SFT → DPO (4.5 M / 250 K pairs). License remains **Apache-2.0** and the context window is **4 096 tokens**. :contentReference[oaicite:0]{index=0}
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---
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## Available files
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| Bits | Format | Size (≈) |
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|------|--------|----------|
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| Q2_K | 2-bit | 3.4 GB |
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| Q3_K_M | 3-bit | 4.4 GB |
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| Q4_0 / Q4_K_M | 4-bit | 5.1 GB / 5.4 GB |
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| Q5_0 / Q5_K_M | 5-bit | 6.1 GB / 6.3 GB |
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| Q6_K | 6-bit | 8 GB* |
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| Q8_0 | 8-bit | 9.3 GB |
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| F16 / F32 | 16 / 32-bit | 17.6 GB | :contentReference[oaicite:1]{index=1}
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\*value shown on the HF page is a placeholder.
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---
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## Quick start (llama.cpp ≥ 0.2)
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```bash
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git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make -j
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./main -m Fanar-1-9B-Instruct.Q4_K_M.gguf -p "ما هي عاصمة قطر؟"
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````
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## Python (llama-cpp-python)
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```python
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from llama_cpp import Llama
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llm = Llama(
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model_path="Fanar-1-9B-Instruct.Q4_K_M.gguf",
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n_ctx=4096,
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chat_format="gemma" # Fanar follows Gemma chat template
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)
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print(llm.create_chat_completion(
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messages=[{"role":"user","content":"Translate 'peace' to Arabic"}]
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).choices[0].message.content)
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```
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---
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### Credits & notes
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* **Original model:** [`QCRI/Fanar-1-9B-Instruct`](https://huggingface.co/QCRI/Fanar-1-9B-Instruct) (please consult its model card for training data, evaluation results and limitations). ([Hugging Face][1])
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* This repository only supplies GGUF conversions for efficient local inference on CPU/GPU; no weights were changed.
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* Use responsibly—outputs may be inaccurate, biased, or culturally sensitive.
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[1]: https://huggingface.co/QCRI/Fanar-1-9B-Instruct?utm_source=chatgpt.com "QCRI/Fanar-1-9B-Instruct - Hugging Face"
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