Instructions to use tweettemposhift/topic-topic_random2_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_random2_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_random2_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random2_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random2_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4cf1a345a93ccb904fd1ec5f9261d51d6247c7a2fe84195c5b313710776578f
- Size of remote file:
- 499 MB
- SHA256:
- 161d40d15104144f7a3f3c2400d2d8b650ee96985607f0ce0c146a3aa5116164
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