Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
sentiment
multilingual
modernbert
sentiment-analysis
product-reviews
place-reviews
text-embeddings-inference
Instructions to use clapAI/roberta-large-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clapAI/roberta-large-multilingual-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clapAI/roberta-large-multilingual-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clapAI/roberta-large-multilingual-sentiment") model = AutoModelForSequenceClassification.from_pretrained("clapAI/roberta-large-multilingual-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "test_f1": 0.8262945499829749, | |
| "test_loss": 0.411376953125, | |
| "test_precision": 0.8271664012247752, | |
| "test_recall": 0.8256432203503072, | |
| "test_runtime": 1038.4953, | |
| "test_samples_per_second": 378.852, | |
| "test_steps_per_second": 0.74 | |
| } |