Instructions to use cunghoctienganh/cad500f4-0ef2-4c87-8146-509eaeb4b09f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cunghoctienganh/cad500f4-0ef2-4c87-8146-509eaeb4b09f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("migtissera/Tess-v2.5-Phi-3-medium-128k-14B") model = PeftModel.from_pretrained(base_model, "cunghoctienganh/cad500f4-0ef2-4c87-8146-509eaeb4b09f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a1cf0d57d1615bfa972029e6ede2016434cc9551b67335e25ed05b0ad6f2a9a
- Size of remote file:
- 112 MB
- SHA256:
- 49492ee2388598812d96e3c77103c4144613922043eb438d0fc710301ba58846
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