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:
- 19e456c3c9d282d9f01eb3128000035682b883222ac71c493dda002b3862b49f
- Size of remote file:
- 3.13 MB
- SHA256:
- 11a5f3105fff5f1337fd566ff057fbe412638294b6ee062af7c20d4e6f6165ec
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