Instructions to use sangmichaelxie/randomselect-roberta-continuedpretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sangmichaelxie/randomselect-roberta-continuedpretrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sangmichaelxie/randomselect-roberta-continuedpretrain")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sangmichaelxie/randomselect-roberta-continuedpretrain") model = AutoModel.from_pretrained("sangmichaelxie/randomselect-roberta-continuedpretrain") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a636eefca1a38198e240fcfdd244551f56fccedc58e15ec2de78ee284d4f6d9
- Size of remote file:
- 499 MB
- SHA256:
- 8f6b3246f6ea47abfe674c77e28422308df2331e091dc6a511cf73d01ecaed51
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