Instructions to use afaji/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afaji/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afaji/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("afaji/results") model = AutoModelForSequenceClassification.from_pretrained("afaji/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 229870b8b64719f5d7067d69bd6682d11caddec64f800f317c2b9ca6dafed9e7
- Size of remote file:
- 5.05 kB
- SHA256:
- ef84754c32989d132cea0dfc5d68c9f48a2672f02840f833dad4f02dbde21de2
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