---
base_model: cognitivecomputations/dolphincoder-starcoder2-7b
datasets:
- cognitivecomputations/dolphin
- jondurbin/airoboros-2.2.1
- cognitivecomputations/dolphin-coder
- teknium/openhermes
- ise-uiuc/Magicoder-OSS-Instruct-75K
- ise-uiuc/Magicoder-Evol-Instruct-110K
- m-a-p/Code-Feedback
- m-a-p/CodeFeedback-Filtered-Instruction
- microsoft/orca-math-word-problems-200k
language:
- en
library_name: transformers
license: bigcode-openrail-m
quantized_by: mradermacher
---
## About

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static quants of https://huggingface.co/cognitivecomputations/dolphincoder-starcoder2-7b

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weighted/imatrix quants are available at https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-i1-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/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q2_K.gguf) | Q2_K | 3.0 |  |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q3_K_S.gguf) | Q3_K_S | 3.4 |  |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.IQ4_XS.gguf) | IQ4_XS | 4.2 |  |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q3_K_L.gguf) | Q3_K_L | 4.3 |  |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.3 | fast on arm, low quality |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q4_K_S.gguf) | Q4_K_S | 4.4 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q4_K_M.gguf) | Q4_K_M | 4.7 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q5_K_S.gguf) | Q5_K_S | 5.2 |  |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q5_K_M.gguf) | Q5_K_M | 5.4 |  |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q6_K.gguf) | Q6_K | 6.2 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.Q8_0.gguf) | Q8_0 | 8.0 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/dolphincoder-starcoder2-7b-GGUF/resolve/main/dolphincoder-starcoder2-7b.f16.gguf) | f16 | 14.9 | 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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