Instructions to use trangtrannnnn/157b4cb8-2091-4cbe-a7ed-a1fcefb36e7c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/157b4cb8-2091-4cbe-a7ed-a1fcefb36e7c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-v0.3") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/157b4cb8-2091-4cbe-a7ed-a1fcefb36e7c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 388b3fcdb5dc447627185eee880a826638ecb337d578c9019398a3d9a3740702
- Size of remote file:
- 6.78 kB
- SHA256:
- e2bbf14963c736dd58e7aaaa2525cd83f69336232edca8c182d25a43163d529b
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