Instructions to use mrHungddddh/3695715c-1fd9-4e91-bce5-d2d78da13133 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrHungddddh/3695715c-1fd9-4e91-bce5-d2d78da13133 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4") model = PeftModel.from_pretrained(base_model, "mrHungddddh/3695715c-1fd9-4e91-bce5-d2d78da13133") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 926ec24b1f880def4b16b7486d0b729487552dafa93547dc5a8335ad144b1f47
- Size of remote file:
- 6.78 kB
- SHA256:
- b31dbcda09ca8623b0bfcc9e7dbbb7e60a2f5ab9cc4b06359873631b1364ff30
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