Instructions to use hf-internal-testing/tiny-random-IBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-IBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-IBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-IBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-IBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4686e82b10cf916de208bc246dd30851ea038ff920598fe59079ac9b2a830c0e
- Size of remote file:
- 729 kB
- SHA256:
- 1168bdf9710b37c3d4598e86941a132bc361c13335b6eaa2e340d6c6de6bd814
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