Instructions to use cardiffnlp/roberta-base-topic-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/roberta-base-topic-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/roberta-base-topic-multi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/roberta-base-topic-multi") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/roberta-base-topic-multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from cardiffnlp/roberta-base-topic-multi: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/cardiffnlp/roberta-base-topic-multi/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://cardiffnlp/roberta-base-topic-multi/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cardiffnlp/roberta-base-topic-multi/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- d6ca0007d2c3579dc82ff6ce2131f9c577e6b5ca4682d60303c5090a6e727c93
- Size of remote file:
- 499 MB
- SHA256:
- f34fccf848a9fbd23f8db7195491c7a6eea48288498ac3e044f25ceaf2be700a
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