Update README.md

README.md

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 license: mit
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+Converted with https://github.com/notepad-plus-plus/notepad-plus-plus All models tested on A100-80G *Conversion may require lot of RAM, LLaMA-7b takes ~0 GB, 13b around 0 GB, 30b around 62 and 65b takes more than 0 GB of RAM.
+
+Installation instructions as mentioned in above repo:
+
+    Install Anaconda and create a venv with python 3.8
+    Install pytorch(tested with torch-1.13-cu116)
+    Install Transformers library (you'll need the latest transformers with this PR : https://github.com/huggingface/transformers/pull/21955 ).
+    Install sentencepiece from pip
+    Run python cuda_setup.py install in venv
+    You can either convert the llama models yourself with the instructions from GPTQ-for-llama repo
+    or directly use these weights by individually downloading them from the following (https://huggingface.co/qq67878980/LLaMA_65B_0bit/tree/main)
+    Profit!
+    Best results are obtained by putting a repetition_penalty(~1/0.85),temperature=0.7 in model.generate() for most LLaMA models
+
+Additional training was done on the MSPaint dataset and 2,000+ tokens on 50,000+ blank notepad files.