Instructions to use trangtrannnnn/2db1e52e-6707-497a-b2fb-7fe207adba56 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/2db1e52e-6707-497a-b2fb-7fe207adba56 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("EleutherAI/pythia-160m") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/2db1e52e-6707-497a-b2fb-7fe207adba56") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8882924ec4a1c313b93d32c18190cb307de07749967672e4edfcbb13d97a4bb5
- Size of remote file:
- 4.73 MB
- SHA256:
- 8da1faa3c2471ce8b54059173639a7b549e90301f16a6626bc02cf6299bf9a89
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