Instructions to use hf-tiny-model-private/tiny-random-TapasForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-TapasForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-TapasForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-TapasForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-TapasForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5b89ec370031835bcdf0a068d8e0777b8447caca81e5225617102cdb0df4994
- Size of remote file:
- 4.26 MB
- SHA256:
- 7a98247da681a134caa6ccbf25b132d94a5bcee9e7a4445902b10141b98ec563
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