Instructions to use hazem74/firstModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hazem74/firstModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hazem74/firstModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hazem74/firstModel") model = AutoModelForSequenceClassification.from_pretrained("hazem74/firstModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f495d86763f74261ea774a64ea5e1c22bd7ec261101713e850e2b1f1b558d93
- Size of remote file:
- 5.18 kB
- SHA256:
- 626a7793e022b29e882a985e5d75eb764395ddbba593c7f7d0142722b9805b54
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