Instructions to use rasmodev/Covid-19_Sentiment_Analysis_RoBERTa_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_RoBERTa_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_RoBERTa_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rasmodev/Covid-19_Sentiment_Analysis_RoBERTa_Model") model = AutoModelForSequenceClassification.from_pretrained("rasmodev/Covid-19_Sentiment_Analysis_RoBERTa_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38abbc9578b23907413a0cc81630dc5683b94bc92bf38bcc5d412b7bd88c6d45
- Size of remote file:
- 499 MB
- SHA256:
- 337f2ada780ac66e3cfb5386013e9b88ae3e84ee45063a06570c0e23c31f3712
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