Instructions to use research-dump/roberta-base_fold_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta-base_fold_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta-base_fold_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta-base_fold_2") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta-base_fold_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d21e5e9665ae57d9ea4b65abf4012445ee29e4699134fc87dec23abe6d314db1
- Size of remote file:
- 499 MB
- SHA256:
- 46ebb995f3860f34aecc39c243f6250c5dec5c0890a025da66ba91de99cace98
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