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:
- 89e5aade2e3204f4fb62f6d94a8c6b522e8c9f1b66fd5ac806fe2fe698840cfd
- Size of remote file:
- 464 kB
- SHA256:
- 65bc056b84329f1847db4402776582d429761e44a307e15f42b973d39084ef63
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