Instructions to use hf-internal-testing/tiny-random-Data2VecTextForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecTextForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-Data2VecTextForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3e09168e0f198203a0e5cdf5fea0fd717fd42a8d94ccf09fd69a7cd78625459
- Size of remote file:
- 354 kB
- SHA256:
- e9e27b270278c8197c019eb82446e3cb475b266baf637056b00b5a02fe6673e3
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