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Model: ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF
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---
license: apache-2.0
language:
- en
library_name: gguf
pipeline_tag: text-generation
tags:
- gguf
- llama.cpp
- quantized
- qwen3
- reasoning
- unsloth
- text-generation
base_model: ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth
datasets:
- ermiaazarkhalili/claude-reasoning-distillation
---
# Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF
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.
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).
- **Full-precision model:** [Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth](https://huggingface.co/ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth)
- **Base model:** [Qwen3-8B (Unsloth 4-bit)](https://huggingface.co/unsloth/qwen3-8b-unsloth-bnb-4bit)
- **Parameters:** 8B
## Available Quantizations
| Quant | Size | Recommended Use | File |
|-------|------|-----------------|------|
| `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) |
| `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) |
| `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) |
| `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) |
| `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) |
| `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) |
`Q4_K_M` is the recommended default for most users.
## Usage
### Download a single quant
```bash
pip install -U "huggingface_hub[cli]"
hf download ermiaazarkhalili/Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF \
--include "*q4_k_m*.gguf" --local-dir ./Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF
```
### llama.cpp
```bash
# build: https://github.com/ggerganov/llama.cpp
./llama-cli -m ./Qwen3-8B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF/qwen3-8b-sft-claude-opus-reasoning-unsloth.q2_k.gguf \
-p "Solve step by step: What is the sum of the first 10 prime numbers?" -n 512
```
### Ollama
```bash
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?"
```
## Training Outcome
| Metric | Value |
|--------|-------|
| SLURM Job ID | `36885901` |
| Runtime | 40m 30s |
| Final Training Loss | 0.8753 |
| Peak VRAM | 14.23 GB |
| GPU | H100 80GB HBM3 (MIG 3g.40gb) |
## License
APACHE-2.0 — see the [base model](https://huggingface.co/unsloth/qwen3-8b-unsloth-bnb-4bit) for full terms.
## Acknowledgments
- [Unsloth](https://github.com/unslothai/unsloth) for 2x faster fine-tuning
- [llama.cpp](https://github.com/ggerganov/llama.cpp) for GGUF quantization
- Base model developers (unsloth)
- [Compute Canada / DRAC](https://alliancecan.ca/) for HPC resources

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