Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence") model = AutoModelForSequenceClassification.from_pretrained("DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e574ed75a1ec201dfa7f1e8cddfcae2627571738d26cd40803fbd2bd82610c36
- Size of remote file:
- 3.38 kB
- SHA256:
- 55e585f1cb0ea9087111ad00ba223964bf711393fb96ee23ec251eb93d69346a
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