Instructions to use nlptown/bert-base-multilingual-uncased-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlptown/bert-base-multilingual-uncased-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlptown/bert-base-multilingual-uncased-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlptown/bert-base-multilingual-uncased-sentiment") model = AutoModelForSequenceClassification.from_pretrained("nlptown/bert-base-multilingual-uncased-sentiment") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#24)
Browse files- Adding `safetensors` variant of this model (e1f410a314fd334fdc630abd757c228236bd911d)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
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