---
language:
- en
library_name: transformers
license: apache-2.0
tags:
- gpt
- llm
- large language model
- h2o-llmstudio
thumbnail: >-
  https://h2o.ai/etc.clientlibs/h2o/clientlibs/clientlib-site/resources/images/favicon.ico
pipeline_tag: text-generation
quantized_by: h2oai
---

# h2o-danube3-4b-chat-GGUF
- Model creator: [H2O.ai](https://huggingface.co/h2oai)
- Original model: [h2oai/h2o-danube3-4b-chat](https://huggingface.co/h2oai/h2o-danube3-4b-chat)

## Description

This repo contains GGUF format model files for [h2o-danube3-4b-chat](https://huggingface.co/h2oai/h2o-danube3-4b-chat) quantized using [llama.cpp](https://github.com/ggerganov/llama.cpp/) framework.

Table below summarizes different quantized versions of [h2o-danube3-4b-chat](https://huggingface.co/h2oai/h2o-danube3-4b-chat). It shows the trade-off between size, speed and quality of the models.


| Name                             | Quant method                      | Model size | MT-Bench AVG | Perplexity | Tokens per second |
|:----------------------------------|:----------------------------------:|:----------:|:------------:|:------------:|:-------------------:|
| [h2o-danube3-4b-chat-F16.gguf](https://huggingface.co/h2oai/h2o-danube3-4b-chat-GGUF/blob/main/h2o-danube3-4b-chat-F16.gguf)   | F16                              |   7.92 GB   |     6.43     |    6.17    |        479        |
| [h2o-danube3-4b-chat-Q8_0.gguf](https://huggingface.co/h2oai/h2o-danube3-4b-chat-GGUF/blob/main/h2o-danube3-4b-chat-Q8_0.gguf)   | Q8_0                              |  4.21 GB   |     6.49     |    6.17    |        725        |
| [h2o-danube3-4b-chat-Q6_K.gguf](https://huggingface.co/h2oai/h2o-danube3-4b-chat-GGUF/blob/main/h2o-danube3-4b-chat-Q6_K.gguf)   | Q6_K                              |  3.25 GB   |     6.37     |    6.20    |        791        |
| [h2o-danube3-4b-chat-Q5_K_M.gguf](https://huggingface.co/h2oai/h2o-danube3-4b-chat-GGUF/blob/main/h2o-danube3-4b-chat-Q5_K_M.gguf) | Q5_K_M                            |   2.81 GB   |     6.25     |    6.24    |        927        |
| [h2o-danube3-4b-chat-Q4_K_M.gguf](https://huggingface.co/h2oai/h2o-danube3-4b-chat-GGUF/blob/main/h2o-danube3-4b-chat-Q4_K_M.gguf) | Q4_K_M | 2.39 GB   |     6.31     |    6.37    |        967        |
| [h2o-danube3-4b-chat-Q3_K_M.gguf](https://huggingface.co/h2oai/h2o-danube3-4b-chat-GGUF/blob/main/h2o-danube3-4b-chat-Q3_K_M.gguf) | Q3_K_M |    1.94 GB   |     5.87     |    6.99    |       1099        |
| [h2o-danube3-4b-chat-Q2_K.gguf](https://huggingface.co/h2oai/h2o-danube3-4b-chat-GGUF/blob/main/h2o-danube3-4b-chat-Q2_K.gguf)   | Q2_K |  1.51 GB   |     3.71     |    9.42    |       1299        |

Columns in the table are:
* Name -- model name and link
* Quant method -- quantization method
* Model size -- size of the model in gigabytes
* MT-Bench AVG -- [MT-Bench](https://arxiv.org/abs/2306.05685) benchmark score. The score is from 1 to 10, the higher, the better
* Perplexity -- perplexity metric on WikiText-2 dataset. It's reported in a perplexity test from llama.cpp. The lower, the better
* Tokens per second -- generation speed in tokens per second, as reported in a perplexity test from llama.cpp. The higher, the better. Speed tests are done on a single H100 GPU


## Prompt template
```
<|prompt|>Why is drinking water so healthy?</s><|answer|>
```