---
base_model: mosaicml/mpt-30b-chat
datasets:
- camel-ai/code
- ehartford/wizard_vicuna_70k_unfiltered
- anon8231489123/ShareGPT_Vicuna_unfiltered
- timdettmers/openassistant-guanaco
- camel-ai/math
- camel-ai/biology
- camel-ai/chemistry
- camel-ai/ai_society
- jondurbin/airoboros-gpt4-1.2
- LongConversations
- camel-ai/physics
language:
- en
library_name: transformers
license: cc-by-nc-sa-4.0
no_imatrix: '(IQ1_M) ggml_validate_row_data: found inf value at block 89 llama_model_quantize:
  failed to quantize: quantized data validation failed'
quantized_by: mradermacher
tags:
- Composer
- MosaicML
- llm-foundry
---
## About

<!-- ### quantize_version: 2 -->
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<!-- ### vocab_type:  -->
<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/mosaicml/mpt-30b-chat

**no more quants forthcoming, as llama.cpp corrupts them and crashes*

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static quants are available at https://huggingface.co/mradermacher/mpt-30b-chat-GGUF
## Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.

## Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-IQ2_M.gguf) | i1-IQ2_M | 10.2 |  |
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-Q2_K.gguf) | i1-Q2_K | 11.4 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 11.8 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-IQ3_M.gguf) | i1-IQ3_M | 14.6 |  |
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-Q3_K_M.gguf) | i1-Q3_K_M | 15.8 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-Q4_K_S.gguf) | i1-Q4_K_S | 17.2 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-Q4_K_M.gguf) | i1-Q4_K_M | 19.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/mpt-30b-chat-i1-GGUF/resolve/main/mpt-30b-chat.i1-Q6_K.gguf) | i1-Q6_K | 24.7 | practically like static Q6_K |

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

## FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

## Thanks

I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

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