Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
unsloth
text-embeddings-inference
Instructions to use PiGrieco/OpenSesame with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PiGrieco/OpenSesame with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PiGrieco/OpenSesame")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PiGrieco/OpenSesame") model = AutoModelForSequenceClassification.from_pretrained("PiGrieco/OpenSesame", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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README.md
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**Overview:**
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"Open Sesame" is an advanced open-source model designed to detect users' buying intentions from textual data.
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**Core Features:**
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- **Intent Detection:** Utilizes a fine-tuned version of RoBERTa to analyze text and identify potential buying signals, enhancing the accuracy and relevance of generated insights.
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- **Integration Capability:** Engineered to be seamlessly integrated into any LLM or AI agent, "Open Sesame" offers a plug-and-play solution for developers looking to enhance e-commerce and retail applications.
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**Overview:**
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"Open Sesame" is an advanced open-source model designed to detect users' buying intentions from textual data.
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LABEL 0 = User hasn't buying intentions.
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LABEL 1 = User has buying intentions.
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**Core Features:**
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- **Intent Detection:** Utilizes a fine-tuned version of RoBERTa to analyze text and identify potential buying signals, enhancing the accuracy and relevance of generated insights.
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- **Integration Capability:** Engineered to be seamlessly integrated into any LLM or AI agent, "Open Sesame" offers a plug-and-play solution for developers looking to enhance e-commerce and retail applications.
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