Instructions to use classla/xlm-roberta-base-multilingual-text-genre-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/xlm-roberta-base-multilingual-text-genre-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="classla/xlm-roberta-base-multilingual-text-genre-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("classla/xlm-roberta-base-multilingual-text-genre-classifier") model = AutoModelForSequenceClassification.from_pretrained("classla/xlm-roberta-base-multilingual-text-genre-classifier") - Notebooks
- Google Colab
- Kaggle
Inquiry About the Availability of the Model distilbert-base-multilingual-cased-sentim-goemotions
I hope this message finds you well.
I recently tried to access the model distilbert-base-multilingual-cased-sentim-goemotions on Hugging Face, but the page returns a 404 error. Could you please confirm if this model is still available? If it has been removed, is there any way to obtain it, or are there alternative models you would recommend for multilingual sentiment and emotion analysis based on GoEmotions?
Thank you very much for your assistance.
Hello!
We’re not the developers of the distilbert-base-multilingual-cased-sentim-goemotions model, so unfortunately we’re unable to assist directly with its availability or access. There is a large selection of models that were fine-tuned on the GoEmotions dataset on HuggingFace, you might find an appropriate alternative in this list: https://huggingface.co/models?dataset=dataset:google-research-datasets/go_emotions