Feature Extraction
Transformers
PyTorch
English
roberta
social media
contrastive learning
text-embeddings-inference
Instructions to use UBC-NLP/InfoDCL-emoji with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/InfoDCL-emoji with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="UBC-NLP/InfoDCL-emoji")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/InfoDCL-emoji") model = AutoModel.from_pretrained("UBC-NLP/InfoDCL-emoji") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 304a83c855ae3f3cfe3f7450ea719e2bfafc3fb3564cf1c92a932d6e7e2ad3b7
- Size of remote file:
- 2.48 kB
- SHA256:
- 2b076631fba6b86a0c27fd256bdef2b9fd63f3b07cff3a8a549a4b0e74963a2e
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