Instructions to use nblinh/cdf861c6-72a4-41b4-ac3f-a9bb00013b19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh/cdf861c6-72a4-41b4-ac3f-a9bb00013b19 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama-chat") model = PeftModel.from_pretrained(base_model, "nblinh/cdf861c6-72a4-41b4-ac3f-a9bb00013b19") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 220d356ca8c8c3a8a0ade0cf7e8628532395e01aa981aad7a626f58c2bced326
- Size of remote file:
- 50.5 MB
- SHA256:
- 49e1e4a57939c404c9edbd09f39bc29763f198810fd58e9c54dda9d912fe1934
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