Instructions to use malteos/aspect-scibert-task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malteos/aspect-scibert-task with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="malteos/aspect-scibert-task")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("malteos/aspect-scibert-task") model = AutoModel.from_pretrained("malteos/aspect-scibert-task") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34d24ef6bdaa492d56aaee92282553ccfa2272b682d0e4616423dc72fb340270
- Size of remote file:
- 440 MB
- SHA256:
- 8a41c6701535b52a8c54a092cf4e189f1ce52721979277b44e988c37dc5cf7e7
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