Text Classification
Transformers
Safetensors
roberta
purchase-intention
intent-detection
lead-scoring
text-embeddings-inference
Instructions to use agusdac/yt-comment-purchase-intent-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agusdac/yt-comment-purchase-intent-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agusdac/yt-comment-purchase-intent-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agusdac/yt-comment-purchase-intent-roberta") model = AutoModelForSequenceClassification.from_pretrained("agusdac/yt-comment-purchase-intent-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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datasets:
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- custom-600-comments
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pipeline_tag: text-classification
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# Purchase Intent Lead Scorer (DistilRoBERTa-base)
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datasets:
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- custom-600-comments
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pipeline_tag: text-classification
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widget:
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- text: "I am definitely going to buy this product tomorrow!"
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example_title: "Purchase Intent"
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- text: "Nice cat!"
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example_title: "Informational"
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# Purchase Intent Lead Scorer (DistilRoBERTa-base)
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