Instructions to use rasmodev/Covid-19_Sentiment_Analysis_BERT_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rasmodev/Covid-19_Sentiment_Analysis_BERT_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rasmodev/Covid-19_Sentiment_Analysis_BERT_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rasmodev/Covid-19_Sentiment_Analysis_BERT_Model") model = AutoModelForSequenceClassification.from_pretrained("rasmodev/Covid-19_Sentiment_Analysis_BERT_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e4bc352870e6f4acacd40fd8d37f69265bdc82ad27dd6e3dffec66081c80bab
- Size of remote file:
- 433 MB
- SHA256:
- 5bac28a71fc32b905987ce041984045becbb269938a6a4035e0d36fd9cf008e8
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