Update README.md

README.md

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----
-license: other
-license_name: mnpl
-license_link: https://mistral.ai/licenses/MNPL-0.1.md
----
+---
+license: other
+license_name: mnpl
+license_link: https://mistral.ai/licenses/MNPL-0.1.md
+tags:
+- code
+language:
+- code
+---
+
+# Pure quantizations of `Codestral-22B-v0.1` for [mistral.java](https://github.com/mukel/mistral.java).
+
+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.  
+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:
+
+```
+./quantize --pure ./Codestral-22B-v0.1-F32.gguf ./Codestral-22B-v0.1-Q4_0.gguf Q4_0
+```
+
+Original model: [https://huggingface.co/mistralai/Codestral-22B-v0.1](https://huggingface.co/mistralai/Codestral-22B-v0.1)
+
+****Note that this model does not support a System prompt.**
+
+
+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:
+- As instruct, for instance to answer any questions about a code snippet (write documentation, explain, factorize) or to generate code following specific indications
+- 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)
+
+