Instructions to use eeeebbb2/9affdde3-b794-49ba-807f-c318c64bc1be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/9affdde3-b794-49ba-807f-c318c64bc1be 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, "eeeebbb2/9affdde3-b794-49ba-807f-c318c64bc1be") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51a7eddc381a9cb057751b5f1381dca834e95da3cbcceabd90c39fa2aa646a0d
- Size of remote file:
- 97.7 kB
- SHA256:
- b3973a0f9d7c32a1f11a983c03e3c06e699a5963006bd5cf51952bcf66136fef
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