Text Classification
Transformers
PyTorch
sentiment-head
feature-extraction
sentiment-analysis
openai-embeddings
custom_code
Instructions to use marcovise/TextEmbedding3SmallSentimentHead with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcovise/TextEmbedding3SmallSentimentHead with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcovise/TextEmbedding3SmallSentimentHead", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("marcovise/TextEmbedding3SmallSentimentHead", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json with huggingface_hub
Browse files- config.json +2 -2
config.json
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"positive": 2
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"auto_map": {
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"AutoConfig": "modeling_te3s_head
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"AutoModel": "modeling_te3s_head
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}
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"positive": 2
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},
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"auto_map": {
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"AutoConfig": "modeling_te3s_head.TextEmbedding3SmallSentimentHeadConfig",
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"AutoModel": "modeling_te3s_head.TextEmbedding3SmallSentimentHead"
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}
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}
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