Instructions to use tweettemposhift/topic-topic_random1_seed2-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_seed2-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_seed2-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random1_seed2-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random1_seed2-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50dc5f3da72f6e692bcde6bf7bec4d712bcaf31b560bc2cea5ae25bcdf687721
- Size of remote file:
- 499 MB
- SHA256:
- 46c6330835294b397614ee70ff7426c61bc5b37470d47ba574616542e48f0955
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