Instructions to use hf-tiny-model-private/tiny-random-ConvBertForSequenceClassification 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-ConvBertForSequenceClassification 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-ConvBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d087e2030e4655c3ca145ec22d3e031ee928cd21d1e796f486482390ee25bd62
- Size of remote file:
- 5.34 MB
- SHA256:
- 8c6939f19951a52bb8e1a82ecee5a742f4a65e41eadda5a69bddd77990abf555
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