Instructions to use gArthur98/Distilbert-For-Capstone_WD_0.07 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gArthur98/Distilbert-For-Capstone_WD_0.07 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gArthur98/Distilbert-For-Capstone_WD_0.07")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gArthur98/Distilbert-For-Capstone_WD_0.07") model = AutoModelForSequenceClassification.from_pretrained("gArthur98/Distilbert-For-Capstone_WD_0.07", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4932c22c03110149ce632dcfaafe49603a08444eecc7b41c8c72491c88c3ed87
- Size of remote file:
- 4.09 kB
- SHA256:
- e0e929a7f9724b601132802b9ada02ce261c3f072d422760f4f74b496da597c8
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