4.5 KiB
4.5 KiB
base_model, library_name, license, pipeline_tag, tags, quantized_by, extra_gated_heading, extra_gated_prompt, extra_gated_button_content
| base_model | library_name | license | pipeline_tag | tags | quantized_by | extra_gated_heading | extra_gated_prompt | extra_gated_button_content | |
|---|---|---|---|---|---|---|---|---|---|
| google/gemma-2-9b | transformers | gemma | text-generation |
|
fedric95 | Access Gemma on Hugging Face | To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately. | Acknowledge license |
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