Text Classification
Transformers
PyTorch
Safetensors
Enawené-Nawé
roberta
text-regression
anger
emotion
emotion intensity
text-embeddings-inference
Instructions to use garrettbaber/twitter-roberta-base-anger-intensity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use garrettbaber/twitter-roberta-base-anger-intensity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="garrettbaber/twitter-roberta-base-anger-intensity")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("garrettbaber/twitter-roberta-base-anger-intensity") model = AutoModelForSequenceClassification.from_pretrained("garrettbaber/twitter-roberta-base-anger-intensity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from garrettbaber/twitter-roberta-base-anger-intensity: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/garrettbaber/twitter-roberta-base-anger-intensity/resolve/main/model.safetensors
- Command line
-
hf download hf://garrettbaber/twitter-roberta-base-anger-intensity/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/garrettbaber/twitter-roberta-base-anger-intensity/resolve/main/model.safetensors
499 MB
- Xet hash:
- ed841339ec73a447a4aa870f48d365f81af4fcce0f175888fc9a9b3436a772f1
- Size of remote file:
- 499 MB
- SHA256:
- 72679b14b9ca4b1065059a5c8953d679a08d290a91223077e7dd9e300a675940
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