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gemma-2-9b-GGUF/README.md
ModelHub XC 2e06fcb8e4 初始化项目,由ModelHub XC社区提供模型
Model: fedric95/gemma-2-9b-GGUF
Source: Original Platform
2026-06-22 13:21:34 +08:00

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---
base_model: google/gemma-2-9b
library_name: transformers
license: gemma
pipeline_tag: text-generation
tags:
- conversational
quantized_by: fedric95
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: To access Gemma on Hugging Face, youre required to review and
agree to Googles usage license. To do this, please ensure youre logged in to Hugging
Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
---
## Llamacpp Quantizations of Meta-Llama-3.1-8B
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b3583">b3583</a> for quantization.
Original model: https://huggingface.co/google/gemma-2-9b
## Download a file (not the whole branch) from below:
| Filename | Quant type | File Size | Perplexity (wikitext-2-raw-v1.test) |
| -------- | ---------- | --------- | ----------- |
| [gemma-2-9b.FP32.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b.FP32.gguf) | FP32 | 37.00GB | 6.9209 +/- 0.04660 |
| [gemma-2-9b-Q8_0.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q8_0.gguf) | Q8_0 | 9.83GB | 6.9222 +/- 0.04660 |
| [gemma-2-9b-Q6_K.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q6_K.gguf) | Q6_K | 7.59GB | 6.9353 +/- 0.04675 |
| [gemma-2-9b-Q5_K_M.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q5_K_M.gguf) | Q5_K_M | 6.65GB | 6.9571 +/- 0.04687 |
| [gemma-2-9b-Q5_K_S.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q5_K_S.gguf) | Q5_K_S | 6.48GB | 6.9623 +/- 0.04690 |
| [gemma-2-9b-Q4_K_M.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q4_K_M.gguf) | Q4_K_M | 5.76GB | 7.0220 +/- 0.04737 |
| [gemma-2-9b-Q4_K_S.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q4_K_S.gguf) | Q4_K_S | 5.48GB | 7.0622 +/- 0.04777 |
| [gemma-2-9b-Q3_K_L.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q3_K_L.gguf) | Q3_K_L | 5.13GB | 7.2144 +/- 0.04910 |
| [gemma-2-9b-Q3_K_M.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q3_K_M.gguf) | Q3_K_M | 4.76GB | 7.2849 +/- 0.04970 |
| [gemma-2-9b-Q3_K_S.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q3_K_S.gguf) | Q3_K_S | 4.34GB | 7.6869 +/- 0.05373 |
| [gemma-2-9b-Q2_K.gguf](https://huggingface.co/fedric95/gemma-2-9b-GGUF/blob/main/gemma-2-9b-Q2_K.gguf) | Q2_K | 3.81GB | 8.7979 +/- 0.06191 |
## Benchmark Results
Results have been computed using:
[hellaswage_val_full](https://raw.githubusercontent.com/klosax/hellaswag_text_data/main/hellaswag_val_full.txt)
[winogrande-debiased-eval](https://huggingface.co/datasets/ikawrakow/winogrande-eval-for-llama.cpp/raw/main/winogrande-debiased-eval.csv)
[mmlu-validation](https://huggingface.co/datasets/ikawrakow/validation-datasets-for-llama.cpp/resolve/main/mmlu-validation.bin)
| Benchmark | Quant type | Metric |
| -------- | ---------- | --------- |
| WinoGrande (0-shot) | Q8_0 | 74.4278 +/- 1.2261 |
| WinoGrande (0-shot) | Q4_K_M | 74.8224 +/- 1.2198 |
| WinoGrande (0-shot) | Q3_K_M | 74.1910 +/- 1.2298 |
| WinoGrande (0-shot) | Q3_K_S | 72.6125 +/- 1.2533 |
| WinoGrande (0-shot) | Q2_K | 71.4286 +/- 1.2697 |
| HellaSwag (0-shot) | Q8_0 | 78.39075881 |
| HellaSwag (0-shot) | Q4_K_M | 77.87293368 |
| HellaSwag (0-shot) | Q3_K_M | 76.64807807 |
| HellaSwag (0-shot) | Q3_K_S | 76.08046206 |
| HellaSwag (0-shot) | Q2_K | 73.07309301 |
| MMLU (0-shot) | Q8_0 | 42.5065 +/- 1.2569 |
| MMLU (0-shot) | Q4_K_M | 42.5065 +/- 1.2569 |
| MMLU (0-shot) | Q3_K_M | 41.3437 +/- 1.2520 |
| MMLU (0-shot) | Q3_K_S | 40.5685 +/- 1.2484 |
| MMLU (0-shot) | Q2_K | 38.1137 +/- 1.2348 |
## Downloading using huggingface-cli
First, make sure you have hugginface-cli installed:
```
pip install -U "huggingface_hub[cli]"
```
Then, you can target the specific file you want:
```
huggingface-cli download fedric95/gemma-2-9b-GGUF --include "gemma-2-9b-Q4_K_M.gguf" --local-dir ./
```
If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
```
huggingface-cli download fedric95/gemma-2-9b-GGUF --include "gemma-2-9b-Q8_0.gguf/*" --local-dir gemma-2-9b-Q8_0
```
You can either specify a new local-dir (gemma-2-9b-Q8_0) or download them all in place (./)
## Reproducibility
https://github.com/ggerganov/llama.cpp/discussions/9020#discussioncomment-10335638