Instructions to use CreatorPhan/Bloomz_lora_answer_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CreatorPhan/Bloomz_lora_answer_v2 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_v2") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-600/optimizer.pt from CreatorPhan/Bloomz_lora_answer_v2: direct link, hf CLI and curl.
- Browser
- Download file 78.8 MB
-
https://huggingface.co/CreatorPhan/Bloomz_lora_answer_v2/resolve/main/checkpoint-600/optimizer.pt
- Command line
-
hf download hf://CreatorPhan/Bloomz_lora_answer_v2/checkpoint-600/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CreatorPhan/Bloomz_lora_answer_v2/resolve/main/checkpoint-600/optimizer.pt
78.8 MB
- Xet hash:
- 37917c79dc3ed6604ef1a37ec45c057e37422aff704cd3a5ad718f3c68a55065
- Size of remote file:
- 78.8 MB
- SHA256:
- a67c0a0a04a16e60dc6df9ce52ee43c4b51d5e34c198de23f6afed8ff5bd6d3e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.