Instructions to use tweettemposhift/topic-topic_random3_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_random3_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_random3_seed2-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random3_seed2-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random3_seed2-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b216f39a62c008634bed4d1e27bcdcd2bb1856b5fc5c1d33dacd7c1510fd8eda
- Size of remote file:
- 499 MB
- SHA256:
- b2a18096ed2eb83f9ce06be296f68e91f8594b5552ceebd29bbfbb495438fe2b
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