Instructions to use nhungphammmmm/ceb56c87-e3f9-4437-a4ac-a6d50d3ef973 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhungphammmmm/ceb56c87-e3f9-4437-a4ac-a6d50d3ef973 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct") model = PeftModel.from_pretrained(base_model, "nhungphammmmm/ceb56c87-e3f9-4437-a4ac-a6d50d3ef973") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e0cf38c47fa1d7ea6a7f039aa62c204445e5c09774994d3e7326636b26e12e6
- Size of remote file:
- 50.4 MB
- SHA256:
- 6eb30f512ae0171c044cf6ece1bb692ea03eaecc215c271f755a71e1c59fb8b2
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