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:
- c643ec982faa6dd2e799d5ac6bc58ea49bf571b6ccbdd8f7c46c95b73d61ea54
- Size of remote file:
- 4.03 kB
- SHA256:
- 1bb8cc257378c99158c80913fbebb85a36ed8b741470d8b8352616f0932e100e
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