Instructions to use Ahmed235/distilbert_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmed235/distilbert_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmed235/distilbert_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmed235/distilbert_classification") model = AutoModelForSequenceClassification.from_pretrained("Ahmed235/distilbert_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52cb6e9822b579e6d1dfa1bc78dbc1dba2bbc176dd2e2a33c62f1d025d04d05e
- Size of remote file:
- 4.79 kB
- SHA256:
- 3f76f7a3218cab7832cb2a3713ebeb9ce2988aa6edda9ce4316f9ed0c109c74d
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