AIArchiveInfo/sales-conversion-model-reinf-learning

reinforcement-learning model by AIArchiveInfo

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[](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT) A reinforcement learning model trained to analyze sales conversations and predict conversion probability evolution turn-by-turn. Specializes in tracking how each message impacts sales success using advanced PPO and LLM-powered metrics. Paper: SalesRLAgent: A Reinforcement Learning Approach for Real-Time Sales Conversion Prediction and Optimization Author: Nandakishor M Published: arXiv:2503.23303 Output: According to the research paper, this model achieves: Each turn analysis provides detailed metrics: This model implements the SalesRLAgent approach described in the research paper. Key innovations include: The model identifies…

AIArchiveInfo/sales-conversion-model-reinf-learning on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. Sales Conversation Analysis Model - Turn-by-Turn Prediction
  2. 🚀 Quick Start with This Model
  3. Installation
  4. Method 1: Direct URL Download (Easiest)
  5. Method 2: Clone Repository (For Offline Use)
  6. 🎯 Model Architecture & Features
  7. Technical Details
  8. Key Capabilities
  9. 📊 Model Performance
  10. Training Data
  11. 💡 Use Cases
  12. 1. Sales Training & Coaching

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Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

AIArchiveInfo/sales-conversion-model-reinf-learning is a reinforcement-learning model repository published by AIArchiveInfo on Hugging Face. The source reports the stable-baselines3 library.

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Model facts

Task
reinforcement-learning
Library
stable-baselines3
Recent downloads (30 days)
0
Cumulative likes
0
Hugging Face trending score
0
Reported safetensors parameters
Not reported
Architecture
Not reported
License
mit
Access
Not gated by Hugging Face
Created
2026-09-21T06:29:50.000Z
Last modified
2026-09-21T06:29:52.000Z

Compatibility and lineage

Reported languages: en

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-09-21T06:36:48.800Z. Daily imports are snapshots, not real-time monitoring.

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