Instructions to use tom-beer/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tom-beer/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tom-beer/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tom-beer/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("tom-beer/my_awesome_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa59c2463fea6c446ef48d8782bea7bb3fec49bf2aeeb569c5212e2a4dffc7d7
- Size of remote file:
- 3.38 kB
- SHA256:
- 75663b7f5502d9f5486671b9a0af463f8dbdd3ce0345ef2cbc0fea05c91f6e98
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