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
- Xet hash:
- b2c96c2bfcbc698244d6544baa03c4acfe28663b5e7a2e6ba3f1359b890e9cd8
- Size of remote file:
- 669 MB
- SHA256:
- e72c9084bf53cee1f722b1acc6f7439cce27e9beabddce447653a1af45405183
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