Instructions to use minhtrannnn/e7ba432e-209c-4efd-8c5c-b6a63524930d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhtrannnn/e7ba432e-209c-4efd-8c5c-b6a63524930d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jingyeom/seal3.1.6n_7b") model = PeftModel.from_pretrained(base_model, "minhtrannnn/e7ba432e-209c-4efd-8c5c-b6a63524930d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40452b1bbcf2d53beb98eb0e9a9dcf37d16772be3bd780a03d8a7937b0085c35
- Size of remote file:
- 6.78 kB
- SHA256:
- 92895dd8a97820438e0b073d8ea06e04f07ac4aec6be798b29219e0d15e0a8f2
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