Instructions to use hf-internal-testing/tiny-random-MobileBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MobileBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MobileBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MobileBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7d8e31d4e1235534c86a36cfa2b1c23de65378af3e060efac952b3e7bfc4181
- Size of remote file:
- 2.82 MB
- SHA256:
- e0510977b1346f1805bc71eca8fad273bb66fd93ba86ba3f6829584520816444
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