Text Classification
Transformers
Safetensors
modernbert
sentiment
multilingual
sentiment-analysis
product-reviews
place-reviews
mmbert
text-embeddings-inference
Instructions to use clapAI/mmBERT-small-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clapAI/mmBERT-small-multilingual-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clapAI/mmBERT-small-multilingual-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clapAI/mmBERT-small-multilingual-sentiment") model = AutoModelForSequenceClassification.from_pretrained("clapAI/mmBERT-small-multilingual-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc46dacdce590ae8ffd8dd3400e53a40431f49e45d50e49acb61b82283c233e6
- Size of remote file:
- 7.12 kB
- SHA256:
- e5252a16c19bf54ea148f149434099397df0937df96458694863c8f3affe5559
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