Instructions to use eceunal/test-model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eceunal/test-model3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eceunal/test-model3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eceunal/test-model3") model = AutoModelForSequenceClassification.from_pretrained("eceunal/test-model3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d999605514dce5b1eb18abb6dc42f44834f33c0d582d40c419933086a6f798a
- Size of remote file:
- 737 MB
- SHA256:
- 1d053cf54b1b8fccdd1770227388edc287038a13a9b41cf55ba61c7cb9d089de
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