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---
base_model: google/medgemma-4b-it
extra_gated_button_content: Acknowledge license
extra_gated_heading: Access MedGemma on Hugging Face
extra_gated_prompt: To access MedGemma on Hugging Face, you're required to review
and agree to [Health AI Developer Foundation's terms of use](https://developers.google.com/health-ai-developer-foundations/terms).
To do this, please ensure you're logged in to Hugging Face and click below. Requests
are processed immediately.
language:
- en
library_name: transformers
license: other
license_link: https://developers.google.com/health-ai-developer-foundations/terms
license_name: health-ai-developer-foundations
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- medical
- radiology
- clinical-reasoning
- dermatology
- pathology
- ophthalmology
- chest-x-ray
---
## About
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<!-- ### convert_type: hf -->
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static quants of https://huggingface.co/google/medgemma-4b-it
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#medgemma-4b-it-GGUF).***
weighted/imatrix quants are available at https://huggingface.co/mradermacher/medgemma-4b-it-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/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.7 | multi-modal supplement |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.mmproj-f16.gguf) | mmproj-f16 | 1.0 | multi-modal supplement |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q2_K.gguf) | Q2_K | 1.8 | |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q3_K_S.gguf) | Q3_K_S | 2.0 | |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q3_K_M.gguf) | Q3_K_M | 2.2 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q3_K_L.gguf) | Q3_K_L | 2.3 | |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.IQ4_XS.gguf) | IQ4_XS | 2.4 | |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q4_K_S.gguf) | Q4_K_S | 2.5 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q4_K_M.gguf) | Q4_K_M | 2.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q5_K_S.gguf) | Q5_K_S | 2.9 | |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q5_K_M.gguf) | Q5_K_M | 2.9 | |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q6_K.gguf) | Q6_K | 3.3 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.Q8_0.gguf) | Q8_0 | 4.2 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/medgemma-4b-it-GGUF/resolve/main/medgemma-4b-it.f16.gguf) | f16 | 7.9 | 16 bpw, overkill |
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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