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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee88e106091a8f6afa49fe073e991f1dbf821cb4a1656de5ea313b6f82007b55
- Size of remote file:
- 5.49 MB
- SHA256:
- faf58ffa8944b2f8571a5d98c61667214e29d7b910c809efbaa7dc7f50fc0a5d
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