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:
- 43f1215e94ee5085c0b7f0bd4276ccaf1bce4e510268c6ecc465191f23a11208
- Size of remote file:
- 4.75 MB
- SHA256:
- 989606bbdea8ab38a7c0d5bca10f28be79603cf14b5cff49ec57ce4bb735330c
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