Instructions to use hf-tiny-model-private/tiny-random-IBertForSequenceClassification 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-IBertForSequenceClassification 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-IBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-IBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-IBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e15fb21a85490649fe1ad478e64434b6aed66892b05cda22849f4946222a9349
- Size of remote file:
- 818 kB
- SHA256:
- 3b28324b773b1ea08f1d65063f5c2fe0dc6a6628c100e1c790ea14005471bcf7
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