Instructions to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForSequenceClassification 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-RobertaPreLayerNormForSequenceClassification 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-RobertaPreLayerNormForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc6064ec1b0910b4e2549121195ba7824a31d1286fea064cb809ca4fa3352351
- Size of remote file:
- 477 kB
- SHA256:
- 23e31ea0cc591336195f8f350acccd6f93fd3880feb857fcde5c2c16b0063eea
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