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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e2a06455f6334627fd2c5088c2e8283d5d7b57126fdcdac5c6b39bebf9a02d3
- Size of remote file:
- 5.49 MB
- SHA256:
- 6efad091a51b8b2041fc84f7c5da87c926ef634692bf0293d0b73b4fe9540c78
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