Instructions to use surrey-nlp/En-Ta_Mono-AG-Llama-2-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use surrey-nlp/En-Ta_Mono-AG-Llama-2-13b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-13b-chat-hf") model = PeftModel.from_pretrained(base_model, "surrey-nlp/En-Ta_Mono-AG-Llama-2-13b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5ac91f8bba81937ac568d39da193d2abb0e349b7c74c0800fd239701180134c
- Size of remote file:
- 173 MB
- SHA256:
- 7a466b40f07cef7b1da5f9e74d5393fc6c429bbc1efe6c2cd95362a34abc5d8d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.