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")# pip install -U transformers accelerate # 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
Commit History
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Upload RobertaForSequenceClassification
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Adding `safetensors` variant of this model (#4)
- Adding `safetensors` variant of this model (779b21287806bd4e708962a00b8999188b241061) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>610f873