Instructions to use gArthur98/Capstone-DistilBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gArthur98/Capstone-DistilBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gArthur98/Capstone-DistilBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gArthur98/Capstone-DistilBert") model = AutoModelForSequenceClassification.from_pretrained("gArthur98/Capstone-DistilBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5a3325aac600b6cc6eddac52467f3f2c8e9ab768509b18f4e2c91caace63750
- Size of remote file:
- 268 MB
- SHA256:
- d49a4b60377bc5382efcfece64a25c4ebf0d06390b91581f3f014815799882a3
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