Instructions to use hf-tiny-model-private/tiny-random-NystromformerForSequenceClassification 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-NystromformerForSequenceClassification 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-NystromformerForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-NystromformerForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-NystromformerForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9ddfa73f6fe61658f4037f4dee7cdcb71b8264f6c2703f2790717052392f9fb
- Size of remote file:
- 4.09 MB
- SHA256:
- 7a33ad700577d5f47c1843e259ee99c18c51d97632772b635b27ac822f5bd27a
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