Instructions to use ashmitg/model_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ashmitg/model_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-1b7") model = PeftModel.from_pretrained(base_model, "ashmitg/model_lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e5b782304ff0e897b9eb3168c7396699b96481aabdad68b7a1150b57f18250a
- Size of remote file:
- 6.31 MB
- SHA256:
- d0a22b4495125eb6d30e2e9461c366cc7bf814141363d61578251cc4c8d24f26
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.