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model_card.md
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| 1 |
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---
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| 2 |
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language:
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| 3 |
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- en
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| 4 |
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license: mit
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tags:
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- conversational
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| 7 |
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- emotional-intelligence
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| 8 |
+
- brello-ei
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| 9 |
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- epic-systems
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| 10 |
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- ai-assistant
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| 11 |
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- empathy
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| 12 |
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- mental-health
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| 13 |
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- support
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| 14 |
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pipeline_tag: text-generation
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+
---
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| 16 |
+
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| 17 |
+
# Brello EI 0 - Emotional Intelligence AI Model
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| 18 |
+
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| 19 |
+
**Created by Epic Systems | Engineered by Rehan Temkar**
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| 20 |
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+
A conversational AI model designed for emotional intelligence and empathetic responses. Brello EI 0 is part of the Brello AI family, bringing human-like emotional understanding to AI conversations.
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## π Features
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| 24 |
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- **Emotional Intelligence**: Designed for empathetic, understanding responses
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- **Conversational**: Natural dialogue flow and engagement
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- **Local Operation**: Can run completely locally
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| 28 |
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- **Memory Efficient**: Optimized for limited hardware
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- **Easy Integration**: Simple API for quick integration
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| 30 |
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## π¦ Installation
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```bash
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pip install torch transformers accelerate
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```
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## π― Quick Start
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| 38 |
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```python
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from brello_ei_0 import BrelloEI0
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# Load the model
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model = BrelloEI0(
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model_path="microsoft/DialoGPT-medium",
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| 45 |
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load_in_4bit=False
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| 46 |
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)
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| 47 |
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| 48 |
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# Generate emotionally intelligent response
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| 49 |
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response = model.generate_response("I'm feeling really stressed about my presentation tomorrow.")
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| 50 |
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print(response)
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| 51 |
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```
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| 52 |
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## π¬ Example Conversations
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| 54 |
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```python
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# Anxiety Support
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response = model.generate_response("I'm feeling really anxious about my job interview tomorrow.")
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| 58 |
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# Output: "I can understand how nerve-wracking job interviews can be..."
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| 59 |
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| 60 |
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# Celebrating Success
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| 61 |
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response = model.generate_response("I just got promoted at work!")
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| 62 |
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# Output: "That's wonderful! I can feel your excitement..."
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| 63 |
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| 64 |
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# Emotional Support
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| 65 |
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response = model.generate_response("I'm feeling lonely and isolated.")
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| 66 |
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# Output: "I'm so sorry you're feeling this way..."
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| 67 |
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```
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| 68 |
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## π― Use Cases
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| 70 |
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### Emotional Support
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| 72 |
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- Providing empathetic responses to stress and anxiety
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| 73 |
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- Supporting users through difficult life transitions
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| 74 |
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- Celebrating achievements and successes
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| 75 |
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| 76 |
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### Personal Development
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| 77 |
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- Career guidance and decision-making support
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| 78 |
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- Life goal exploration and planning
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| 79 |
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- Self-reflection and emotional awareness
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| 80 |
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| 81 |
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### Mental Health Support
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| 82 |
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- Stress management and coping strategies
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| 83 |
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- Emotional validation and understanding
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| 84 |
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- Positive reinforcement and encouragement
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| 85 |
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| 86 |
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## βοΈ Configuration
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| 87 |
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| 88 |
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### Model Parameters
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| 89 |
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- `model_path`: Path to base model (default: "microsoft/DialoGPT-medium")
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| 90 |
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- `device`: Device to load model on ('cuda', 'cpu', etc.)
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| 91 |
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- `load_in_4bit`: Enable 4-bit quantization for memory efficiency
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| 92 |
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- `load_in_8bit`: Enable 8-bit quantization for memory efficiency
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| 93 |
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| 94 |
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### Generation Parameters
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| 95 |
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- `temperature`: Sampling temperature (default: 0.7)
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| 96 |
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- `top_p`: Top-p sampling parameter (default: 0.9)
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| 97 |
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- `max_length`: Maximum response length (default: 4096)
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| 98 |
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- `min_length`: Minimum response length (default: 30)
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| 99 |
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- `max_new_tokens`: Maximum new tokens to generate (default: 256)
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| 100 |
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| 101 |
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## π Performance
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| 102 |
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| 103 |
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### Model Specifications
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| 104 |
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- **Foundation**: Microsoft DialoGPT-medium
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| 105 |
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- **Parameters**: 345 Million
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| 106 |
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- **Context Length**: 1024 tokens
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| 107 |
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- **Training**: Conversational dialogue data
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| 108 |
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- **Optimization**: Emotional intelligence focus
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| 109 |
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| 110 |
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### Memory Requirements
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| 111 |
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- **Full Precision**: ~1GB VRAM
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| 112 |
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- **8-bit Quantization**: ~500MB VRAM
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| 113 |
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- **4-bit Quantization**: ~250MB VRAM (recommended)
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| 114 |
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| 115 |
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## ποΈ Architecture
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| 116 |
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| 117 |
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Brello EI 0 is built on advanced language model architecture with the following key components:
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| 118 |
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| 119 |
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- **Base Model**: Microsoft DialoGPT-medium
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| 120 |
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- **Tokenizer**: Optimized for conversational data
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| 121 |
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- **Generation**: Emotionally intelligent response patterns
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| 122 |
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- **Post-processing**: Response cleaning and enhancement
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| 123 |
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- **Quantization**: 4-bit for memory efficiency (optional)
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| 124 |
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| 125 |
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## π€ Contributing
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| 126 |
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| 127 |
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This model is part of the Epic Systems AI initiative. For questions or contributions, please contact the development team.
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| 128 |
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| 129 |
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## π License
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| 130 |
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| 131 |
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This project is licensed under the MIT License - see the LICENSE file for details.
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| 132 |
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| 133 |
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## π Acknowledgments
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| 134 |
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| 135 |
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- **Epic Systems** for the vision and support
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| 136 |
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- **Rehan Temkar** for engineering and development
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| 137 |
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- **Microsoft** for the DialoGPT foundation model
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| 138 |
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- **Hugging Face** for the transformers library
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| 139 |
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| 140 |
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---
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| 141 |
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| 142 |
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**Brello EI 0** - Bringing emotional intelligence to AI conversations πβ¨
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