A LLaMA 2 model is implemented in the PyTorch framework from scratch.

1. Ensure the required libraries are installed on your system.

pip install -r requirements.txt

2. Download model weights with the official llama repository or from LLaMA 2 7B on Hugging Face. Make sure to include the following:

pytorch-llama
├── llama-2-7b
│   ├── checklist.chk
│   ├── consolidated.00.pth
│   └── params.json
├── tokenizer.model

1. pytorch-llama
2. llama
3. LLaMA 2 7B on Hugging Face
4. Root Mean Square Layer Normalization
5. RoFormer: Enhanced Transformer with Rotary Position Embedding
6. Fast Transformer Decoding: One Write-Head is All You Need
7. GLU Variants Improve Transformer