Instructions to use abidlabs/test_push_output_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abidlabs/test_push_output_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abidlabs/test_push_output_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abidlabs/test_push_output_2") model = AutoModelForSequenceClassification.from_pretrained("abidlabs/test_push_output_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a9e2a4946a877163b898b32e4ce9e156401441c6e4b8acdffc00a7c70d22635
- Size of remote file:
- 5.14 kB
- SHA256:
- fd190f5eaa134c4f1e2a6eec5cf599fdb86a9d832f04ab1b06822e7597d81e27
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