Feature Extraction
Transformers
PyTorch
English
xlm-roberta
social media
contrastive learning
text-embeddings-inference
Instructions to use UBC-NLP/InfoDCL-Emoji-XLMR-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/InfoDCL-Emoji-XLMR-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="UBC-NLP/InfoDCL-Emoji-XLMR-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/InfoDCL-Emoji-XLMR-Base") model = AutoModelForMultimodalLM.from_pretrained("UBC-NLP/InfoDCL-Emoji-XLMR-Base") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot