Instructions to use dada22231/1e4d9a96-1e67-4e04-9a16-545c4c1d68a1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/1e4d9a96-1e67-4e04-9a16-545c4c1d68a1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceM4/tiny-random-LlamaForCausalLM") model = PeftModel.from_pretrained(base_model, "dada22231/1e4d9a96-1e67-4e04-9a16-545c4c1d68a1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de1ba3c1ddb78c57554b380f3f86002e3c8072944b1ca184640b7f13f2c2e055
- Size of remote file:
- 97.7 kB
- SHA256:
- 4872e256b4b2a4ca415b34e0ba1de91befc0186cf3a1a18d0d18f262e4cf1540
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