Instructions to use rajaswa-postman/es_chat_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rajaswa-postman/es_chat_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "rajaswa-postman/es_chat_lora") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from rajaswa-postman/es_chat_lora: direct link, hf CLI and curl.
- Browser
- Download file 67.2 MB
-
https://huggingface.co/rajaswa-postman/es_chat_lora/resolve/main/optimizer.pt
- Command line
-
hf download hf://rajaswa-postman/es_chat_lora/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/rajaswa-postman/es_chat_lora/resolve/main/optimizer.pt
67.2 MB
- Xet hash:
- 7a6488d1990f2451d4ad3f5d3cc59df736987ee7233c571ba191ad47e157e238
- Size of remote file:
- 67.2 MB
- SHA256:
- c73feed2ba79154ba34bf5b3b9df4843f62e207e769643c8c03c21abe01ed78a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.