Instructions to use avkumararun/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avkumararun/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avkumararun/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avkumararun/results") model = AutoModelForSequenceClassification.from_pretrained("avkumararun/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af579b2587e01657c1c4168f2afa1d46ca4634f87a9f3c9c456de22c39f6a847
- Size of remote file:
- 5.2 kB
- SHA256:
- 861d4c7a1cc85622dce4475145c485ff7bbed18258de676f2782be919813af24
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