Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
sentiment
multilingual
modernbert
sentiment-analysis
product-reviews
place-reviews
text-embeddings-inference
Instructions to use clapAI/roberta-base-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clapAI/roberta-base-multilingual-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clapAI/roberta-base-multilingual-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clapAI/roberta-base-multilingual-sentiment") model = AutoModelForSequenceClassification.from_pretrained("clapAI/roberta-base-multilingual-sentiment") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 4
Browse files
model.safetensors
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