Instructions to use junujunu/roberta-base-vts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junujunu/roberta-base-vts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="junujunu/roberta-base-vts")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("junujunu/roberta-base-vts") model = AutoModel.from_pretrained("junujunu/roberta-base-vts") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
config.json
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"_name_or_path": "./checkpoint-
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"_name_or_path": "./pretrain/model/checkpoint-747208/",
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pytorch_model.bin
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size 442540845
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