Instructions to use cardiffnlp/roberta-base-tweet-topic-multi-2020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/roberta-base-tweet-topic-multi-2020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/roberta-base-tweet-topic-multi-2020")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/roberta-base-tweet-topic-multi-2020") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/roberta-base-tweet-topic-multi-2020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from cardiffnlp/roberta-base-tweet-topic-multi-2020: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/cardiffnlp/roberta-base-tweet-topic-multi-2020/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://cardiffnlp/roberta-base-tweet-topic-multi-2020/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/cardiffnlp/roberta-base-tweet-topic-multi-2020/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 41f783a355586e5add706bdeb4e7e7b58067deb848dbaabfa19aa5dd0738ab17
- Size of remote file:
- 499 MB
- SHA256:
- 3575115d5c001472ad76d0096a1435477d1e3bddcbb951a6833c8e418ae97ff2
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