Instructions to use cunghoctienganh/43052dda-7ecb-4c93-ba18-fd4292a6b5e4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cunghoctienganh/43052dda-7ecb-4c93-ba18-fd4292a6b5e4 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, "cunghoctienganh/43052dda-7ecb-4c93-ba18-fd4292a6b5e4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dba32cb4c46ff4be9074c04ef38e8236e8984d6632f289563fc06cee5879437
- Size of remote file:
- 6.78 kB
- SHA256:
- 87dc0ae74f4356b1398b4f260322acb8b3069ca1b4fa35c1ef8fb5312a106dc3
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