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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e85486e99fb745df9bcb2d248b6a88fd55ff900b6a3e43b8349a0f16a8fd806e
- Size of remote file:
- 1.2 MB
- SHA256:
- 3139c099cfaa8afaec7d48be2dde41909c3421153d57994cccca26cd1cde72d8
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