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--- |
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license: other |
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license_name: mnpl |
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license_link: https://mistral.ai/licenses/MNPL-0.1.md |
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tags: |
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- code |
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language: |
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- code |
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--- |
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# Pure quantizations of `Codestral-22B-v0.1` for [mistral.java](https://github.com/mukel/mistral.java). |
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In the wild, Q8_0 quantizations are fine, but Q4_0 quantizations are rarely pure e.g. the output.weights tensor is quantized with Q6_K, instead of Q4_0. |
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A pure Q4_0 quantization can be generated from a high precision (F32, F16, BFLOAT16) .gguf source with the quantize utility from llama.cpp as follows: |
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``` |
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./quantize --pure ./Codestral-22B-v0.1-F32.gguf ./Codestral-22B-v0.1-Q4_0.gguf Q4_0 |
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``` |
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Original model: [https://huggingface.co/mistralai/Codestral-22B-v0.1](https://huggingface.co/mistralai/Codestral-22B-v0.1) |
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****Note that this model does not support a System prompt.** |
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Codestrall-22B-v0.1 is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash (more details in the [Blogpost](https://mistral.ai/news/codestral/)). The model can be queried: |
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- As instruct, for instance to answer any questions about a code snippet (write documentation, explain, factorize) or to generate code following specific indications |
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- As Fill in the Middle (FIM), to predict the middle tokens between a prefix and a suffix (very useful for software development add-ons like in VS Code) |
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