Instructions to use Svenkevs/FirstModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Svenkevs/FirstModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Svenkevs/FirstModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Svenkevs/FirstModel") model = AutoModelForSequenceClassification.from_pretrained("Svenkevs/FirstModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57f1ea3d73bf01807af56112748d2bb5f356e3412294ac285bd6ff1ac56f4046
- Size of remote file:
- 433 MB
- SHA256:
- f437a30f80f57374d62041a23bb2e4293b4ccd3265f9bfea7508b28900743aef
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