Instructions to use hf-internal-testing/tiny-random-BertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BertForSequenceClassification") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12f472a981bd95c6a9e9a67e78368e9f9f94f89b14efd49b5d024f967fa7d089
- Size of remote file:
- 481 kB
- SHA256:
- 0e255ab2176ebd0119739d00b1682574f4125807259c8b6837dd73552d09dfd2
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