metadata
base_model: google/gemma-2-9b
library_name: transformers
license: gemma
pipeline_tag: text-generation
tags:
- conversational
quantized_by: fedric95
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Llamacpp Quantizations of Meta-Llama-3.1-8B
Using llama.cpp release b3583 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 | FP32 | 37.00GB | 6.9209 +/- 0.04660 |
| gemma-2-9b-Q8_0.gguf | Q8_0 | 9.83GB | 6.9222 +/- 0.04660 |
| gemma-2-9b-Q6_K.gguf | Q6_K | 7.59GB | 6.9353 +/- 0.04675 |
| gemma-2-9b-Q5_K_M.gguf | Q5_K_M | 6.65GB | 6.9571 +/- 0.04687 |
| gemma-2-9b-Q5_K_S.gguf | Q5_K_S | 6.48GB | 6.9623 +/- 0.04690 |
| gemma-2-9b-Q4_K_M.gguf | Q4_K_M | 5.76GB | 7.0220 +/- 0.04737 |
| gemma-2-9b-Q4_K_S.gguf | Q4_K_S | 5.48GB | 7.0622 +/- 0.04777 |
| gemma-2-9b-Q3_K_L.gguf | Q3_K_L | 5.13GB | 7.2144 +/- 0.04910 |
| gemma-2-9b-Q3_K_M.gguf | Q3_K_M | 4.76GB | 7.2849 +/- 0.04970 |
| gemma-2-9b-Q3_K_S.gguf | Q3_K_S | 4.34GB | 7.6869 +/- 0.05373 |
| gemma-2-9b-Q2_K.gguf | Q2_K | 3.81GB | 8.7979 +/- 0.06191 |
Benchmark Results
Results have been computed using:
| 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