auto-patch README.md

README.md

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+---
+base_model: google/medgemma-27b-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
+quantized_by: mradermacher
+tags:
+- medical
+- x-ray
+- pathology
+- dermatology
+- fundus
+- radiology report generation
+- chest-x-ray
+- medical-embeddings
+- image-classification
+- zero-shot-image-classification
+- image-feature-extraction
+- image-text-to-text
+---
+## About
+
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
 <!-- ### vocab_type:  -->
 <!-- ### tags:  -->
 static quants of https://huggingface.co/google/medgemma-27b-it
+
+<!-- provided-files -->
+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/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q2_K.gguf) | Q2_K | 10.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q3_K_S.gguf) | Q3_K_S | 12.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q3_K_M.gguf) | Q3_K_M | 13.5 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q3_K_L.gguf) | Q3_K_L | 14.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q4_K_S.gguf) | Q4_K_S | 15.8 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q4_K_M.gguf) | Q4_K_M | 16.6 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q6_K.gguf) | Q6_K | 22.3 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q8_0.gguf) | Q8_0 | 28.8 | fast, best quality |
+
+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.
+
+<!-- end -->