Feature Extraction
Transformers
PyTorch
Safetensors
English
bert
sentiment-analysis
text-classification
generic
sentiment-classification
text-embeddings-inference
Instructions to use numind/NuSentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numind/NuSentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="numind/NuSentiment")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("numind/NuSentiment") model = AutoModel.from_pretrained("numind/NuSentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 161ce667afccf799fc05937df199fb7287bbf66cca782405a70535457ea81876
- Size of remote file:
- 438 MB
- SHA256:
- dec0759250235c83f497c5ca8f8908aa9dda65c4be631b6c49999f8efee15e1e
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