Instructions to use hf-internal-testing/tiny-random-ConvBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-ConvBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ConvBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-ConvBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79b49173c6971262f4247a1cb067e15776f2ff205ec6a4b0b6b282b02d0ee656
- Size of remote file:
- 5.34 MB
- SHA256:
- 58086cc580b3d580dbc7e8d46e8a4d9af1bc99a765514c97d54ce8f2fa8574c5
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