Update README.md

README.md

@@ -19,34 +19,37 @@ quantized_by: OptimizeLLM
 
 This is Mistral AI's Mixtral Instruct v0.1 model, quantized on 02/24/2024. The file size is slightly larger than TheBloke's version from December, and it seems to work well.
 
-How to quantize your own models on Windows and an RTX GPU:
+# How to quantize your own models on Windows and an RTX GPU:
 
-Requirements:
-	- git and python installed (if you use oobabooga etc you are probably already good to go)
+## Requirements:
+* Make sure you have git and python installed (if you use oobabooga etc you are probably good to go)
 
 The following example starts at the root of D drive and quantizes mistral's Mixtral-9x7B-Instruct-v0.1:
 
-In Windows command prompt: 
-D:
-mkdir Mixtral
-git clone https://github.com/ggerganov/llama.cpp
+# Instructions:
 
+## Windows command prompt
+* D:
+* mkdir Mixtral
+* git clone https://github.com/ggerganov/llama.cpp
+
+## Download llama.cpp
 Assuming you want CUDA for your NVIDIA RTX GPU(s) use the links below, or grab latest compiled executables from https://github.com/ggerganov/llama.cpp/releases
 Latest version as of Feb 24, 2024:
-https://github.com/ggerganov/llama.cpp/releases/download/b2253/cudart-llama-bin-win-cu12.2.0-x64.zip
-https://github.com/ggerganov/llama.cpp/releases/download/b2253/llama-b2253-bin-win-cublas-cu12.2.0-x64.zip
+* https://github.com/ggerganov/llama.cpp/releases/download/b2253/cudart-llama-bin-win-cu12.2.0-x64.zip
+* https://github.com/ggerganov/llama.cpp/releases/download/b2253/llama-b2253-bin-win-cublas-cu12.2.0-x64.zip
 
 Extract the two .zip files directly into the llama.cpp folder you just git cloned. Overwrite files as prompted.
 
+## Download Mixtral
 Download the full-blast version of the model by downloading all .safetensors, .json, and .model files to D:\Mixtral\
 https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
 Download all .safetensors, .json, and .model files to D:\Mixtral\
 
-Convert the model to fp16:
+## Convert the model to fp16:
 D:\llama.cpp>python convert.py D:\Mixtral --outtype f16 --outfile D:\Mixtral\Mixtral-8x7B-Instruct-v0.1.fp16.bin
 
-Quantize the fp16 model to q5_k_m:
-
+## Quantize the fp16 model to q5_k_m:
 D:\llama.cpp>quantize.exe D:\Mixtral\Mixtral-8x7B-Instruct-v0.1.fp16.bin D:\Mixtral\Mixtral-8x7B-Instruct-v0.1.q5_k_m.gguf q5_k_m
 
 That's it. Load up the resulting .gguf file like you normally would.