Instructions to use CreatorPhan/Bloomz_lora_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CreatorPhan/Bloomz_lora_answer with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloomz-3b") model = PeftModel.from_pretrained(base_model, "CreatorPhan/Bloomz_lora_answer") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-200/optimizer.pt from CreatorPhan/Bloomz_lora_answer: direct link, hf CLI and curl.
- Browser
- Download file 78.8 MB
-
https://huggingface.co/CreatorPhan/Bloomz_lora_answer/resolve/main/checkpoint-200/optimizer.pt
- Command line
-
hf download hf://CreatorPhan/Bloomz_lora_answer/checkpoint-200/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CreatorPhan/Bloomz_lora_answer/resolve/main/checkpoint-200/optimizer.pt
78.8 MB
- Xet hash:
- ea5221584aeacbdc9826c0d35804927029f8e3232afc19b7e5eec33880b76357
- Size of remote file:
- 78.8 MB
- SHA256:
- 6d7f250b734db4b40976d1847121f325e5f8e4aa321a8357abe3dc127b5fc83a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.