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
Adding `safetensors` variant of this model
#4
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7ebcb76b3f07232363899380041708419247753d2b293be452c87e8560cf5561
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size 498615900
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