Instructions to use rasgaard/20newsgroups-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rasgaard/20newsgroups-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rasgaard/20newsgroups-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rasgaard/20newsgroups-distilbert") model = AutoModelForSequenceClassification.from_pretrained("rasgaard/20newsgroups-distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48ae5d70bd0666b35d30b3fb073e2e20e13f8d17bca4ee71e1a85e2ddf1ca105
- Size of remote file:
- 268 MB
- SHA256:
- 6a4fe6d6f6c6cb5f024a9224cd7bcc303fed94e74dbde645d23a43dd32d1ccdf
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