Instructions to use hf-tiny-model-private/tiny-random-MobileBertForSequenceClassification 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-MobileBertForSequenceClassification 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-MobileBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2a4251c50def725c445c26edb42fb8a387b6e07cda012daa86618a09106221d
- Size of remote file:
- 2.87 MB
- SHA256:
- 93bbc4c065755222e0a2439671e13da400272e80ede2f5b4af591cf8f7f3f092
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