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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c393779dd3cfe2b35ce8e07882484af9712437defa6fafab60a81c6b73d133b1
- Size of remote file:
- 4.28 MB
- SHA256:
- 758fd91591b6ba7e434db1529b9e239472c652c47c31d5359b7c3373b910ab06
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