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README.md

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+---
+base_model:
+- mistralai/Mistral-7B-Instruct-v0.2
+- NousResearch/Yarn-Mistral-7b-128k
+- Kukedlc/MyModelsMerge-7b
+exported_from: Kukedlc/NeuralContext-7b-v2
+language:
+- en
+library_name: transformers
+quantized_by: mradermacher
+tags:
+- merge
+- mergekit
+- lazymergekit
+- mistralai/Mistral-7B-Instruct-v0.2
+- NousResearch/Yarn-Mistral-7b-128k
+- Kukedlc/MyModelsMerge-7b
+---
+## About
+
 static quants of https://huggingface.co/Kukedlc/NeuralContext-7b-v2
+
+
+<!-- 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/NeuralContext-7b-v2-GGUF/resolve/main/NeuralContext-7b-v2.Q3_K_M.gguf) | Q3_K_M | 3.8 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/NeuralContext-7b-v2-GGUF/resolve/main/NeuralContext-7b-v2.Q4_K_S.gguf) | Q4_K_S | 4.4 | fast, recommended |
+
+
+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
+
+## 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.
+
+<!-- end -->