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
File size: 231 Bytes
4bbfd02 | 1 | {"eval_loss": 0.8723608255386353, "eval_f1": 0.6931034482758621, "eval_f1_macro": 0.692628774202147, "eval_accuracy": 0.6931034482758621, "eval_runtime": 18.2192, "eval_samples_per_second": 382.016, "eval_steps_per_second": 47.752} |