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---
base_model: microsoft/Phi-3.5-MoE-instruct
language:
- multilingual
library_name: transformers
license: mit
license_link: https://huggingface.co./microsoft/Phi-3.5-MoE-instruct/resolve/main/LICENSE
no_imatrix: 'quantize: line 230: 3149156 Segmentation fault'
quantized_by: mradermacher
tags:
- nlp
- code
---
## About
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static quants of https://huggingface.co./microsoft/Phi-3.5-MoE-instruct
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## 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/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q2_K.gguf) | Q2_K | 15.4 | |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q3_K_S.gguf) | Q3_K_S | 18.2 | |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q3_K_M.gguf) | Q3_K_M | 20.1 | lower quality |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q3_K_L.gguf) | Q3_K_L | 21.8 | |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.IQ4_XS.gguf) | IQ4_XS | 22.7 | |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q4_K_S.gguf) | Q4_K_S | 23.9 | fast, recommended |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q4_K_M.gguf) | Q4_K_M | 25.4 | fast, recommended |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q5_K_S.gguf) | Q5_K_S | 28.9 | |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q5_K_M.gguf) | Q5_K_M | 29.8 | |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q6_K.gguf) | Q6_K | 34.5 | very good quality |
| [GGUF](https://huggingface.co./mradermacher/Phi-3.5-MoE-instruct-GGUF/resolve/main/Phi-3.5-MoE-instruct.Q8_0.gguf) | Q8_0 | 44.6 | fast, best quality |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
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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