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:
- ef95cb4d9019f91b39ebdc287bc36c37e37905c80a3d8fd3fbacdd7dbaed0ec1
- Size of remote file:
- 4.38 MB
- SHA256:
- 1bb68894fcd4008832a8649975e9ebf125178d60d5e27e77d8ce18556a4da694
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