Text Classification
Transformers
Safetensors
English
distilbert
shopping
deals
classification
e-commerce
recommendation
text-embeddings-inference
Instructions to use selvaonline/shopping-assistant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selvaonline/shopping-assistant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selvaonline/shopping-assistant")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selvaonline/shopping-assistant") model = AutoModelForSequenceClassification.from_pretrained("selvaonline/shopping-assistant") - Notebooks
- Google Colab
- Kaggle
Upload requirements.txt with huggingface_hub
Browse files- requirements.txt +6 -0
requirements.txt
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numpy>=1.24.0
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huggingface-hub>=0.16.0
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# For demo scripts
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requests>=2.31.0
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numpy>=1.24.0
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huggingface-hub>=0.16.0
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# For sentence transformers and semantic search
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sentence-transformers>=2.2.2
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# For zero-shot classification
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accelerate>=0.20.0
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# For demo scripts
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requests>=2.31.0
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