Instructions to use GoatMilk98/635-a2-ibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GoatMilk98/635-a2-ibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="GoatMilk98/635-a2-ibert")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("GoatMilk98/635-a2-ibert") model = AutoModelForQuestionAnswering.from_pretrained("GoatMilk98/635-a2-ibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51757cd8ad14ca27e74214beb09514be38aa3a14f84aacb4736a2ae87cc5de0c
- Size of remote file:
- 993 MB
- SHA256:
- f71467bc2fe2fce9e8ab46cffdd55bf7c98f529e9954e66f314feb81a6c9e244
路
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