Instructions to use jaimin/Bullet_Point with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaimin/Bullet_Point with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="jaimin/Bullet_Point")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("jaimin/Bullet_Point") model = AutoModelForQuestionAnswering.from_pretrained("jaimin/Bullet_Point") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc7fd19f6530b09bac74f8d0f1e5262cffc61939421e12361f2a992928c19df4
- Size of remote file:
- 496 MB
- SHA256:
- e0b64ccefc1bcb569b604baea27eb873e5482fdf6eb3ceff1fb5368397db5aed
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