Instructions to use leetdavid/example_workflow_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leetdavid/example_workflow_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leetdavid/example_workflow_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leetdavid/example_workflow_model") model = AutoModelForSequenceClassification.from_pretrained("leetdavid/example_workflow_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a3346fb7297fa8f939f2910932b8e76adbf8ea7f7618907aeb847ca73b8b51a
- Size of remote file:
- 409 MB
- SHA256:
- 543c03772caae0d67d634e485630621f8291617f3f88cded05f97e4f9eadeeb6
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