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:
- 03e13ffed2e409f71f05614ccdd371e04df4ad2b513d40f4d608eb0b28c3ddcb
- Size of remote file:
- 2.87 MB
- SHA256:
- fd290550361143313b588a1679ad92eaebf880c0442e4fdccbdaf47a492deec3
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