Instructions to use JAlexis/bertFast_01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JAlexis/bertFast_01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="JAlexis/bertFast_01")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("JAlexis/bertFast_01") model = AutoModelForQuestionAnswering.from_pretrained("JAlexis/bertFast_01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8978646971430ccb9cb6c1374cda57eb185906643c15b839336c6798775b262b
- Size of remote file:
- 431 MB
- SHA256:
- 05b1e7799d539cb33799a834a2c1aec235daaba18c0bdcdab4893cd8bdc4271a
路
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