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Model: mradermacher/Ministral-8B-Instruct-2410-GGUF
Source: Original Platform

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README.md

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+---
+base_model: mistralai/Ministral-8B-Instruct-2410
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+extra_gated_prompt: |-
+  # Mistral AI Research License
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+  ## 3. Limitations
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+  ## 7. Termination
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+  ## 8. General provisions
+  **8.1. Governing laws.** This Agreement will be governed by the laws of France, without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement.
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+  ## 9. Definitions
+  "Agreement": means this Mistral AI Research License agreement governing the access, use, and Distribution of the Mistral Models, Derivatives and Outputs.
+  "Derivative": means any (i) modified version of the Mistral Model (including but not limited to any customized or fine-tuned version thereof), (ii) work based on the Mistral Model, or (iii) any other derivative work thereof.
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+  "You": means the individual or entity entering into this Agreement with Mistral AI.
+
+  *Mistral AI processes your personal data below to provide the model and enforce its license. If you are affiliated with a commercial entity, we may also send you communications about our models. For more information on your rights and data handling, please see our <a href="https://mistral.ai/terms/">privacy policy</a>.*
+language:
+- en
+- fr
+- de
+- es
+- it
+- pt
+- zh
+- ja
+- ru
+- ko
+library_name: transformers
+license: other
+license_link: https://mistral.ai/licenses/MRL-0.1.md
+license_name: mrl
+mradermacher:
+  readme_rev: 1
+quantized_by: mradermacher
+tags:
+- mistral-common
+---
+## About
+
+<!-- ### quantize_version: 2 -->
+<!-- ### output_tensor_quantised: 1 -->
+<!-- ### convert_type: hf -->
+<!-- ### vocab_type:  -->
+<!-- ### tags: nicoboss -->
+static quants of https://huggingface.co/mistralai/Ministral-8B-Instruct-2410
+
+<!-- provided-files -->
+
+***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Ministral-8B-Instruct-2410-GGUF).***
+
+weighted/imatrix quants are available at https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-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/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q2_K.gguf) | Q2_K | 3.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q3_K_S.gguf) | Q3_K_S | 3.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q3_K_L.gguf) | Q3_K_L | 4.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.IQ4_XS.gguf) | IQ4_XS | 4.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.8 | fast on arm, low quality |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q5_K_S.gguf) | Q5_K_S | 5.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q5_K_M.gguf) | Q5_K_M | 5.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q6_K.gguf) | Q6_K | 6.7 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/Ministral-8B-Instruct-2410-GGUF/resolve/main/Ministral-8B-Instruct-2410.f16.gguf) | f16 | 16.1 | 16 bpw, overkill |
+
+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 -->