Instructions to use tweettemposhift/topic-topic_random1_seed1-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random1_seed1-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random1_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random1_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random1_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b454bf04d452a0d187c4ec622268169dc9ed4ada4339bfc87fe320f56e270aa9
- Size of remote file:
- 499 MB
- SHA256:
- c20a260ada0a7215647a8a3fd9b9787d22c53d8269f22aa80519636425b505db
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