Text Classification
Transformers
TensorBoard
Safetensors
modernbert
sentiment
multilingual
sentiment-analysis
product-reviews
place-reviews
text-embeddings-inference
Instructions to use clapAI/modernBERT-base-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clapAI/modernBERT-base-multilingual-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clapAI/modernBERT-base-multilingual-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clapAI/modernBERT-base-multilingual-sentiment") model = AutoModelForSequenceClassification.from_pretrained("clapAI/modernBERT-base-multilingual-sentiment", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 335f6b1aaac6e79cf8b58a8e44465abdd5dd3624aef04b8db0d7e749a86fa856
- Size of remote file:
- 6.9 kB
- SHA256:
- 38d9b5f118e063e6d69e4823acb821625e842aac8e73c6ebd501f34942ccc41d
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