---
base_model: openbmb/MiniCPM-2B-sft-fp32
language:
- en
- zh
library_name: transformers
license: other
license_link: https://github.com/OpenBMB/General-Model-License/blob/main/%E9%80%9A%E7%94%A8%E6%A8%A1%E5%9E%8B%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE-%E6%9D%A5%E6%BA%90%E8%AF%B4%E6%98%8E-%E5%AE%A3%E4%BC%A0%E9%99%90%E5%88%B6-%E5%95%86%E4%B8%9A%E6%8E%88%E6%9D%83.md
license_name: gml
quantized_by: mradermacher
tags:
- MiniCPM
- ModelBest
- THUNLP
---
## About

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static quants of https://huggingface.co/openbmb/MiniCPM-2B-sft-fp32

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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
## 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/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q2_K.gguf) | Q2_K | 1.3 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.IQ3_XS.gguf) | IQ3_XS | 1.4 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.IQ3_S.gguf) | IQ3_S | 1.5 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q3_K_S.gguf) | Q3_K_S | 1.5 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.IQ3_M.gguf) | IQ3_M | 1.5 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q3_K_M.gguf) | Q3_K_M | 1.6 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.IQ4_XS.gguf) | IQ4_XS | 1.7 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q3_K_L.gguf) | Q3_K_L | 1.7 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q4_K_S.gguf) | Q4_K_S | 1.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q4_K_M.gguf) | Q4_K_M | 1.9 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q5_K_S.gguf) | Q5_K_S | 2.0 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q5_K_M.gguf) | Q5_K_M | 2.1 |  |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q6_K.gguf) | Q6_K | 2.5 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.Q8_0.gguf) | Q8_0 | 3.0 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/MiniCPM-2B-sft-fp32-GGUF/resolve/main/MiniCPM-2B-sft-fp32.f16.gguf) | f16 | 5.6 | 16 bpw, overkill |

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.

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