Instructions to use MilaNLProc/xlm-emo-t with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MilaNLProc/xlm-emo-t with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MilaNLProc/xlm-emo-t")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MilaNLProc/xlm-emo-t") model = AutoModelForSequenceClassification.from_pretrained("MilaNLProc/xlm-emo-t", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin with git-lfs
Browse files- pytorch_model.bin +3 -0
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