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---
base_model: lastmass/Qwen3_Medical_GRPO
tags:
- text-generation-inference
- transformers
- unsloth
- qwen3
- vllm
- medical
- TensorBlock
- GGUF
license: apache-2.0
language:
- en
- zh
datasets:
- FreedomIntelligence/medical-o1-reasoning-SFT
- lastmass/medical-o1-reasoning-SFT-keywords
---

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## lastmass/Qwen3_Medical_GRPO - GGUF

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        Join our Discord to learn more about what we're building ↗
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This repo contains GGUF format model files for [lastmass/Qwen3_Medical_GRPO](https://huggingface.co/lastmass/Qwen3_Medical_GRPO).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5753](https://github.com/ggml-org/llama.cpp/commit/73e53dc834c0a2336cd104473af6897197b96277).

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## Prompt template

```
{system_prompt}<|endoftext|>{prompt}<start_working_out>
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Qwen3_Medical_GRPO-Q2_K.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q2_K.gguf) | Q2_K | 1.669 GB | smallest, significant quality loss - not recommended for most purposes |
| [Qwen3_Medical_GRPO-Q3_K_S.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q3_K_S.gguf) | Q3_K_S | 1.887 GB | very small, high quality loss |
| [Qwen3_Medical_GRPO-Q3_K_M.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q3_K_M.gguf) | Q3_K_M | 2.076 GB | very small, high quality loss |
| [Qwen3_Medical_GRPO-Q3_K_L.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q3_K_L.gguf) | Q3_K_L | 2.240 GB | small, substantial quality loss |
| [Qwen3_Medical_GRPO-Q4_0.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q4_0.gguf) | Q4_0 | 2.370 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Qwen3_Medical_GRPO-Q4_K_S.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q4_K_S.gguf) | Q4_K_S | 2.383 GB | small, greater quality loss |
| [Qwen3_Medical_GRPO-Q4_K_M.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q4_K_M.gguf) | Q4_K_M | 2.497 GB | medium, balanced quality - recommended |
| [Qwen3_Medical_GRPO-Q5_0.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q5_0.gguf) | Q5_0 | 2.824 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Qwen3_Medical_GRPO-Q5_K_S.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q5_K_S.gguf) | Q5_K_S | 2.824 GB | large, low quality loss - recommended |
| [Qwen3_Medical_GRPO-Q5_K_M.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q5_K_M.gguf) | Q5_K_M | 2.890 GB | large, very low quality loss - recommended |
| [Qwen3_Medical_GRPO-Q6_K.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q6_K.gguf) | Q6_K | 3.306 GB | very large, extremely low quality loss |
| [Qwen3_Medical_GRPO-Q8_0.gguf](https://huggingface.co/tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF/blob/main/Qwen3_Medical_GRPO-Q8_0.gguf) | Q8_0 | 4.280 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF --include "Qwen3_Medical_GRPO-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/lastmass_Qwen3_Medical_GRPO-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```