gguf text-generation en arxiv:2009.03300 arxiv:1905.07830 arxiv:1911.11641 arxiv:1904.09728 arxiv:1905.10044 arxiv:1907.10641 arxiv:1811.00937 arxiv:1809.02789 arxiv:1911.01547 arxiv:1705.03551 arxiv:2107.03374 arxiv:2108.07732 arxiv:2110.14168 arxiv:2304.06364 arxiv:2206.04615 arxiv:2009.11462 arxiv:2101.11718 arxiv:2110.08193 arxiv:1804.09301 arxiv:2109.07958 arxiv:1804.06876 arxiv:2203.09509 base_model:google/gemma-7b base_model:quantized:google/gemma-7b license:other region:us
---
base_model: google/gemma-7b
language:
- en
license: other
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
model_name: gemma-7b
pipeline_tag: text-generation
inference: false
model_creator: google
model_type: gemma
quantized_by: brittlewis12
---

# Gemma 7B GGUF

**Original model**: [gemma-7b](https://huggingface.co/google/gemma-7b)

**Model creator**: [google](https://huggingface.co/google)

This repo contains GGUF format model files for Google’s Gemma-7B. 

> Gemma is a family of lightweight, state-of-the-art open models from Google,
> built from the same research and technology used to create the Gemini models.
> They are text-to-text, decoder-only large language models, available in English,
> with open weights, pre-trained variants, and instruction-tuned variants. Gemma
> models are well-suited for a variety of text generation tasks, including
> question answering, summarization, and reasoning. Their relatively small size
> makes it possible to deploy them in environments with limited resources such as
> a laptop, desktop or your own cloud infrastructure, democratizing access to
> state of the art AI models and helping foster innovation for everyone.

Learn more on Google’s [Model page](https://ai.google.dev/gemma/docs).

### What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.
Converted using llama.cpp build 2226 (revision [eccd7a2](https://github.com/ggerganov/llama.cpp/commit/eccd7a26ddbff19e4b8805648f5f14c501957859))

---

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- create & save **Characters** with custom system prompts & temperature settings
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- make it your own with custom **Theme colors**
- powered by Metal ⚡️ & [Llama.cpp](https://github.com/ggerganov/llama.cpp), with **haptics** during response streaming!
- **try it out** yourself today, on [Testflight](https://testflight.apple.com/join/sFWReS7K)!
- follow [cnvrs on twitter](https://twitter.com/cnvrsai) to stay up to date

---

## Original Model Evaluation

| Benchmark                      | Metric        | 2B Params | 7B Params |
| ------------------------------ | ------------- | ----------- | --------- |
| [MMLU](https://arxiv.org/abs/2009.03300)                   | 5-shot, top-1 | 42.3        | 64.3      |
| [HellaSwag](https://arxiv.org/abs/1905.07830)         | 0-shot        |71.4        | 81.2      |
| [PIQA](https://arxiv.org/abs/1911.11641)                   | 0-shot        | 77.3        | 81.2      |
| [SocialIQA](https://arxiv.org/abs/1904.09728)      | 0-shot        | 59.7        | 51.8      |
| [BooIQ](https://arxiv.org/abs/1905.10044)                | 0-shot        | 69.4        | 83.2      |
| [WinoGrande](https://arxiv.org/abs/1907.10641)       | partial score | 65.4        | 72.3      |
| [CommonsenseQA](https://arxiv.org/abs/1811.00937) | 7-shot        | 65.3        | 71.3      |
| [OpenBookQA](https://arxiv.org/abs/1809.02789)       |               | 47.8        | 52.8      |
| [ARC-e](https://arxiv.org/abs/1911.01547)                  |               | 73.2        | 81.5      |
| [ARC-c](https://arxiv.org/abs/1911.01547)                   |               | 42.1        | 53.2      |
| [TriviaQA](https://arxiv.org/abs/1705.03551)           | 5-shot        | 53.2        | 63.4      |
| [Natural Questions](https://github.com/google-research-datasets/natural-questions)  | 5-shot        | -       | 23        |
| [HumanEval](https://arxiv.org/abs/2107.03374)      | pass@1        | 22.0        | 32.3      |
| [MBPP](https://arxiv.org/abs/2108.07732)                   | 3-shot        | 29.2        | 44.4      |
| [GSM8K](https://arxiv.org/abs/2110.14168)                | maj@1         | 17.7        | 46.4      |
| [MATH](https://arxiv.org/abs/2108.07732)                   | 4-shot        | 11.8          | 24.3      |
| [AGIEval](https://arxiv.org/abs/2304.06364)           |               | 24.2        | 41.7      |
| [BIG-Bench](https://arxiv.org/abs/2206.04615)         |               | 35.2        | 55.1      |
| **Average**                    |               | **54.0**    | **56.4**  |

| Benchmark                      | Metric        | 2B Params   | 7B Params |
| ------------------------------ | ------------- | ----------- | --------- |
| [RealToxicity](https://arxiv.org/abs/2009.11462)        | average       | 6.86        | 7.90      |
| [BOLD](https://arxiv.org/abs/2101.11718)                   |               | 45.57       | 49.08     |
| [CrowS-Pairs](https://aclanthology.org/2020.emnlp-main.154/)        | top-1         | 45.82       | 51.33     |
| [BBQ Ambig](https://arxiv.org/abs/2110.08193v2)               | 1-shot, top-1 | 62.58       | 92.54     |
| [BBQ Disambig](https://arxiv.org/abs/2110.08193v2)            | top-1         | 54.62       | 71.99     |
| [Winogender](https://arxiv.org/abs/1804.09301)       | top-1         | 51.25       | 54.17     |
| [TruthfulQA](https://arxiv.org/abs/2109.07958)       |               | 44.84       | 31.81     |
| [Winobias 1_2](https://arxiv.org/abs/1804.06876)       |               | 56.12       | 59.09     |
| [Winobias 2_2](https://arxiv.org/abs/1804.06876)       |               | 91.10       | 92.23     |
| [Toxigen](https://arxiv.org/abs/2203.09509)             |               | 29.77       | 39.59     |

