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:
- 815469e6f99dc51da47f770ef902aa925994448dd72f43c087c5584077e369f5
- Size of remote file:
- 4.07 MB
- SHA256:
- 8ed17a43b202dbbfe80bc45931a0269ba25e9f03f75f9d5f1ce9a91a0e6a285a
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