Instructions to use isashap/final2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use isashap/final2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("gpt2") model = PeftModel.from_pretrained(base_model, "isashap/final2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4374f9c40559161eefe8490201d044b1cd2739fe6752a595bfa201c841c0afc
- Size of remote file:
- 25.3 kB
- SHA256:
- 73707bbc0ace18361553cfc7a7f617096d297489ac6089123a1168fb6414c535
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