Instructions to use suhcrates/yb_model_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suhcrates/yb_model_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="suhcrates/yb_model_dir")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("suhcrates/yb_model_dir") model = AutoModelForQuestionAnswering.from_pretrained("suhcrates/yb_model_dir") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30621e4297a001372fb1708f2d90884f25cdecd2820eeae41d49ed2c432b6c3e
- Size of remote file:
- 3.31 kB
- SHA256:
- 171430dfd8a7ffbc24b7c339e0bf965e3083611df1b1c4746c6677e9c9dcf7cf
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