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:
- b28b650e43ccb049bb2ec362c797d526231b25b0320294514ca22ef88314c9cf
- Size of remote file:
- 6.78 kB
- SHA256:
- c1448cf50f82f0bfcb50e535fcfe67d1fea793ace2cc6af08c350c117ee3b56a
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