Instructions to use epiphacc/csabstract-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use epiphacc/csabstract-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="epiphacc/csabstract-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("epiphacc/csabstract-classification") model = AutoModelForSequenceClassification.from_pretrained("epiphacc/csabstract-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7563e0a85f7e1126ce15d29e608ae92a7620386ad14bc67f4822ddf7e3017eb1
- Size of remote file:
- 3.25 kB
- SHA256:
- 5436dafe4d2834ac698e83dfdba13c167fc13b7a26de2a09670b170492723c4e
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