Instructions to use rasgaard/squeezebert-newsgroups-probe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rasgaard/squeezebert-newsgroups-probe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rasgaard/squeezebert-newsgroups-probe")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rasgaard/squeezebert-newsgroups-probe") model = AutoModelForSequenceClassification.from_pretrained("rasgaard/squeezebert-newsgroups-probe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87a4fb822ac03b80231fd15f8978abc7944ebeade9255083f2a619e8f8110ca8
- Size of remote file:
- 205 MB
- SHA256:
- 71b9d529bd9959c0fd351e64f1cc80406da2eb81d450ac67ae291b2408595f7a
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