80 lines
3.6 KiB
Markdown
80 lines
3.6 KiB
Markdown
---
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base_model: ConicCat/Gemma-3-12B-Fornax-QAT-CoT
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datasets:
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- GeneralReasoning/GeneralThought-430K
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- Undi95/R1-RP-ShareGPT3
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- PJMixers-Dev/Gryphe-Aesir-RPG-Charcards-Opus-Mixed-split-v3-0324
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extra_gated_button_content: Acknowledge license
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extra_gated_heading: Access Gemma on Hugging Face
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extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
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agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging
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Face and click below. Requests are processed immediately.
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language:
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- en
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library_name: transformers
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license: gemma
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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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- gemma3
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- gemma
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- google
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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: nicoboss -->
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weighted/imatrix quants of https://huggingface.co/ConicCat/Gemma-3-12B-Fornax-QAT-CoT
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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#Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF).***
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static quants are available at https://huggingface.co/mradermacher/Gemma-3-12B-Fornax-QAT-CoT-GGUF
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**This is a vision model - mmproj files (if any) will be under files**
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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://www.modelscope.cn/models/mradermacher/Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF/resolve/master/Gemma-3-12B-Fornax-QAT-CoT.i1-IQ2_XS.gguf) | i1-IQ2_XS | 3.9 | |
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| [GGUF](https://www.modelscope.cn/models/mradermacher/Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF/resolve/master/Gemma-3-12B-Fornax-QAT-CoT.i1-IQ3_XS.gguf) | i1-IQ3_XS | 5.3 | |
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| [GGUF](https://www.modelscope.cn/models/mradermacher/Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF/resolve/master/Gemma-3-12B-Fornax-QAT-CoT.i1-IQ4_XS.gguf) | i1-IQ4_XS | 6.7 | |
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| [GGUF](https://www.modelscope.cn/models/mradermacher/Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF/resolve/master/Gemma-3-12B-Fornax-QAT-CoT.i1-Q4_K_M.gguf) | i1-Q4_K_M | 7.4 | fast, recommended |
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| [GGUF](https://www.modelscope.cn/models/mradermacher/Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF/resolve/master/Gemma-3-12B-Fornax-QAT-CoT.i1-Q5_K_M.gguf) | i1-Q5_K_M | 8.5 | |
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| [GGUF](https://www.modelscope.cn/models/mradermacher/Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF/resolve/master/Gemma-3-12B-Fornax-QAT-CoT.i1-Q6_K.gguf) | i1-Q6_K | 9.8 | practically like static Q6_K |
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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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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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