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--- |
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base_model: google/medgemma-27b-it |
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extra_gated_button_content: Acknowledge license |
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extra_gated_heading: Access MedGemma on Hugging Face |
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extra_gated_prompt: To access MedGemma on Hugging Face, you're required to review |
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and agree to [Health AI Developer Foundation's terms of use](https://developers.google.com/health-ai-developer-foundations/terms). |
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To do this, please ensure you're logged in to Hugging Face and click below. Requests |
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are processed immediately. |
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language: en |
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library_name: transformers |
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license: other |
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license_link: https://developers.google.com/health-ai-developer-foundations/terms |
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license_name: health-ai-developer-foundations |
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mradermacher: |
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readme_rev: 1 |
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quantized_by: mradermacher |
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tags: |
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- medical |
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- x-ray |
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- pathology |
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- dermatology |
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- fundus |
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- radiology report generation |
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- chest-x-ray |
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- medical-embeddings |
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- image-classification |
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- zero-shot-image-classification |
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- image-feature-extraction |
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- image-text-to-text |
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--- |
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## About |
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<!-- ### quantize_version: 2 --> |
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<!-- ### output_tensor_quantised: 1 --> |
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<!-- ### convert_type: hf --> |
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<!-- ### vocab_type: --> |
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<!-- ### tags: --> |
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static quants of https://huggingface.co/google/medgemma-27b-it |
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<!-- provided-files --> |
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#medgemma-27b-it-GGUF).*** |
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/medgemma-27b-it-i1-GGUF |
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## Usage |
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If you are unsure how to use GGUF files, refer to one of [TheBloke's |
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for |
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more details, including on how to concatenate multi-part files. |
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## Provided Quants |
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
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| Link | Type | Size/GB | Notes | |
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|:-----|:-----|--------:|:------| |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.7 | multi-modal supplement | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.mmproj-f16.gguf) | mmproj-f16 | 1.0 | multi-modal supplement | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q2_K.gguf) | Q2_K | 10.6 | | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q3_K_S.gguf) | Q3_K_S | 12.3 | | |
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| [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 | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q3_K_L.gguf) | Q3_K_L | 14.6 | | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.IQ4_XS.gguf) | IQ4_XS | 15.0 | | |
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| [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 | |
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| [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 | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q5_K_S.gguf) | Q5_K_S | 18.9 | | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q5_K_M.gguf) | Q5_K_M | 19.4 | | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q6_K.gguf) | Q6_K | 22.3 | very good quality | |
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| [GGUF](https://huggingface.co/mradermacher/medgemma-27b-it-GGUF/resolve/main/medgemma-27b-it.Q8_0.gguf) | Q8_0 | 28.8 | fast, best quality | |
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Here is a handy graph by ikawrakow comparing some lower-quality quant |
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types (lower is better): |
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 |
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And here are Artefact2's thoughts on the matter: |
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 |
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## FAQ / Model Request |
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See https://huggingface.co/mradermacher/model_requests for some answers to |
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questions you might have and/or if you want some other model quantized. |
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## Thanks |
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting |
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me use its servers and providing upgrades to my workstation to enable |
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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. |
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<!-- end --> |
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