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docs/LLaMA-model.md

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+LLaMA is a Large Language Model developed by Meta AI. 
+
+It was trained on more tokens than previous models. The result is that the smallest version with 7 billion parameters has similar performance to GPT-3 with 175 billion parameters.
+
+This guide will cover usage through the official `transformers` implementation. For 4-bit mode, head over to [GPTQ models (4 bit mode)
+](https://github.com/oobabooga/text-generation-webui/wiki/GPTQ-models-(4-bit-mode)).
+
+## Getting the weights
+
+### Option 1: pre-converted weights
+
+* Torrent: https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1484235789
+* Direct download: https://huggingface.co/Neko-Institute-of-Science
+
+⚠️ The tokenizers for the sources above and also for many LLaMA fine-tunes available on Hugging Face may be outdated, so I recommend downloading the following universal LLaMA tokenizer: 
+
+```
+python download-model.py oobabooga/llama-tokenizer
+```
+
+Once downloaded, it will be automatically applied to **every** `LlamaForCausalLM` model that you try to load.
+
+### Option 2: convert the weights yourself
+
+1. Install the `protobuf` library:
+
+```
+pip install protobuf
+```
+
+2. Use the script below to convert the model in `.pth` format that you, a fellow academic, downloaded using Meta's official link:
+
+### [convert_llama_weights_to_hf.py](https://github.com/huggingface/transformers/blob/main/src/transformers/models/llama/convert_llama_weights_to_hf.py)
+
+```
+python convert_llama_weights_to_hf.py --input_dir /path/to/LLaMA --model_size 7B --output_dir /tmp/outputs/llama-7b
+```
+
+3. Move the `llama-7b` folder inside your `text-generation-webui/models` folder.
+
+## Starting the web UI
+
+```python
+python server.py --model llama-7b
+```