Instructions to use ma2za/xlm-roberta-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ma2za/xlm-roberta-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ma2za/xlm-roberta-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ma2za/xlm-roberta-emotion") model = AutoModelForSequenceClassification.from_pretrained("ma2za/xlm-roberta-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2 opened almost 3 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot