Instructions to use minhnguyennnnnn/7f01aeb2-b835-4daa-97b3-181780718c6f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhnguyennnnnn/7f01aeb2-b835-4daa-97b3-181780718c6f 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, "minhnguyennnnnn/7f01aeb2-b835-4daa-97b3-181780718c6f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b27ef3162fca11be91bcb251107a680b09b2015dc76153ec208cd62ad2b8ec8
- Size of remote file:
- 6.78 kB
- SHA256:
- 3d0146ae98955472765d163616971fda17cf63807c6384e4594482c3c5582e6a
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