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Model: ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF Source: Original Platform
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---
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license: apache-2.0
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language:
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- en
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library_name: gguf
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pipeline_tag: text-generation
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tags:
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- gguf
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- llama.cpp
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- quantized
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- qwen3
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- reasoning
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- unsloth
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- text-generation
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base_model: ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth
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datasets:
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- ermiaazarkhalili/claude-reasoning-distillation
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---
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# Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF
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GGUF quantizations of [Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth) for **CPU and edge inference** with [llama.cpp](https://github.com/ggerganov/llama.cpp), [Ollama](https://ollama.com), LM Studio, and other GGUF runtimes.
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This model is a fine-tune of [Qwen3-8B (Unsloth 4-bit)](https://huggingface.co/unsloth/qwen3-8b-unsloth-bnb-4bit) for **reasoning distillation (chain-of-thought)**, trained with [Unsloth](https://github.com/unslothai/unsloth) on [claude-reasoning-distillation](https://huggingface.co/datasets/ermiaazarkhalili/claude-reasoning-distillation).
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- **Full-precision model:** [Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth)
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- **Base model:** [Qwen3-8B (Unsloth 4-bit)](https://huggingface.co/unsloth/qwen3-8b-unsloth-bnb-4bit)
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- **Parameters:** 8B
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## Available Quantizations
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| Quant | Size | Recommended Use | File |
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|-------|------|-----------------|------|
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| `Q2_K` | 3.28 GB | Smallest, lowest quality — quick tests / very constrained devices | [`qwen3-8b-sft-claude-opus-reasoning-unsloth.q2_k.gguf`](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/qwen3-8b-sft-claude-opus-reasoning-unsloth.q2_k.gguf) |
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| `Q3_K_M` | 4.12 GB | Small, acceptable quality | [`qwen3-8b-sft-claude-opus-reasoning-unsloth.q3_k_m.gguf`](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/qwen3-8b-sft-claude-opus-reasoning-unsloth.q3_k_m.gguf) |
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| `Q4_K_M` | 5.03 GB | Recommended — best size/quality balance | [`qwen3-8b-sft-claude-opus-reasoning-unsloth.q4_k_m.gguf`](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/qwen3-8b-sft-claude-opus-reasoning-unsloth.q4_k_m.gguf) |
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| `Q5_K_M` | 5.85 GB | High quality, larger | [`qwen3-8b-sft-claude-opus-reasoning-unsloth.q5_k_m.gguf`](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/qwen3-8b-sft-claude-opus-reasoning-unsloth.q5_k_m.gguf) |
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| `Q6_K` | 6.73 GB | Very high quality, near-fp16 | [`qwen3-8b-sft-claude-opus-reasoning-unsloth.q6_k.gguf`](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/qwen3-8b-sft-claude-opus-reasoning-unsloth.q6_k.gguf) |
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| `Q8_0` | 8.71 GB | Near-lossless, largest | [`qwen3-8b-sft-claude-opus-reasoning-unsloth.q8_0.gguf`](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/blob/main/qwen3-8b-sft-claude-opus-reasoning-unsloth.q8_0.gguf) |
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`Q4_K_M` is the recommended default for most users.
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## Usage
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### Download a single quant
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```bash
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pip install -U "huggingface_hub[cli]"
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hf download ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF \
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--include "*q4_k_m*.gguf" --local-dir ./Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF
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```
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### llama.cpp
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```bash
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# build: https://github.com/ggerganov/llama.cpp
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./llama-cli -m ./Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/qwen3-8b-sft-claude-opus-reasoning-unsloth.q2_k.gguf \
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-p "Solve step by step: What is the sum of the first 10 prime numbers?" -n 512
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```
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### Ollama
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```bash
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ollama run hf.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF:Q4_K_M "Solve step by step: What is the sum of the first 10 prime numbers?"
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```
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## Training Outcome
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| Metric | Value |
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|--------|-------|
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| SLURM Job ID | `36885901` |
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| Runtime | 40m 30s |
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| Final Training Loss | 0.8753 |
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| Peak VRAM | 14.23 GB |
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| GPU | H100 80GB HBM3 (MIG 3g.40gb) |
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## License
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APACHE-2.0 — see the [base model](https://huggingface.co/unsloth/qwen3-8b-unsloth-bnb-4bit) for full terms.
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## Acknowledgments
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- [Unsloth](https://github.com/unslothai/unsloth) for 2x faster fine-tuning
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- [llama.cpp](https://github.com/ggerganov/llama.cpp) for GGUF quantization
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- Base model developers (unsloth)
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- [Compute Canada / DRAC](https://alliancecan.ca/) for HPC resources
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