Instructions to use hf-internal-testing/tiny-random-TapasForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TapasForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-TapasForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-TapasForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-TapasForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 700c3f3f5d8b6f15d694431212ea0693e465e511c2a3093b5cec8bf4acba347e
- Size of remote file:
- 4.26 MB
- SHA256:
- b1bab74819553c16a086866726e5d06b650f11a6ce3dfbc71b85bf8b96f61750
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