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:
- d73004b4532b2280733795d7f81bd6917411b99125400de0898539d66ad64b0c
- Size of remote file:
- 433 MB
- SHA256:
- 7e905f84bd5ec56e000bbc7b39f5b0c0c6af02aa004eee79a75c69e629b9d38d
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