metadata
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-danube3-500m-chat-GGUF
- Model creator: H2O.ai
- Original model: h2oai/h2o-danube3-500m-chat
Description
This repo contains GGUF format model files for h2o-danube3-500m-chat quantized using llama.cpp framework.
Table below summarizes different quantized versions of h2o-danube3-500m-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-danube3-500m-chat-F16.gguf | F16 | 1.03 GB | 3.34 | 9.46 | 1870 |
| h2o-danube3-500m-chat-Q8_0.gguf | Q8_0 | 0.55 GB | 3.76 | 9.46 | 2144 |
| h2o-danube3-500m-chat-Q6_K.gguf | Q6_K | 0.42 GB | 3.77 | 9.46 | 2418 |
| h2o-danube3-500m-chat-Q5_K_M.gguf | Q5_K_M | 0.37 GB | 3.20 | 9.55 | 2430 |
| h2o-danube3-500m-chat-Q4_K_M.gguf | Q4_K_M | 0.32 GB | 3.16 | 9.96 | 2427 |
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 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|>