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:
- 947914b04c03d9dd398a963a146203e7d1d270b86b95f34f23ec102ecdcc9e42
- Size of remote file:
- 3.9 kB
- SHA256:
- bc0e5c9ad0b0ca204d289714c31a7a5453a223799229d7b1aa1e91f433cc4f83
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