Text Classification
Transformers
PyTorch
xlm-roberta
Eval Results (legacy)
text-embeddings-inference
Instructions to use cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#5 opened over 1 year ago
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SFconvertbot
Adding `safetensors` variant of this model
#4 opened over 1 year ago
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SFconvertbot
Adding `safetensors` variant of this model
#3 opened almost 2 years ago
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Librarian Bot: Add base_model information to model
#2 opened about 3 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#1 opened over 3 years ago
by
SFconvertbot