Instructions to use lvcalucioli/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lvcalucioli/results with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("swap-uniba/LLaMAntino-2-7b-hf-ITA") model = PeftModel.from_pretrained(base_model, "lvcalucioli/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 804a2fa5491cb6a59d6ca2f9eb2e777562931559eeb96e476f35ba9449bced0a
- Size of remote file:
- 4.35 kB
- SHA256:
- 5c8303886a7a93befaaf411826a0d4f3579a507fa485dc08ab4119bdea0dfb72
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