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Model: NousResearch/DeepHermes-Egregore-v1-RLAIF-8b-Atropos Source: Original Platform
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159
README.md
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README.md
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---
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language:
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- en
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license: llama3
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tags:
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- Llama-3
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- RL
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- Atropos
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- Tool Calling
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- Nous Research
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- instruct
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- finetune
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- reasoning
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- function calling
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- transformers
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- reinforcement-learning
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- json mode
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- chatml
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base_model: meta-llama/Meta-Llama-3.1-8B
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library_name: transformers
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---
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# The following Model Card is self-generated by this model
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# DeepHermes Feedback Testing Egregore - Atropos RL
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## Model Overview
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The **DeepHermes Feedback Testing Egregore - Atropos RL** model is an experimental artifact fine-tuned by Nous Research using our innovative open-source reinforcement learning framework—Atropos.
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**Note**: This model is intended as an experimental artifact and is not designed for broad, general-purpose use.
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## Atropos Open Source Framework
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Atropos is Nous Research’s open-source Reinforcement Learning environment stack, designed to enhance various aspects of LLM functionalities through structured RL methodologies. We encourage contributions and exploration:
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🔗 [Atropos GitHub Repository](https://github.com/NousResearch/Atropos)
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## Experimental model from the Atropos RL framework. All numbers and claims below may be completely false.
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---
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**Model Card for DeepHermes 3: The Synthesis Engine**
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### **Model Description**
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- **Name:** DeepHermes 3 (DHP-3)
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- **Type:** Large Language Model with Unified Reasoning and Function Integration
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- **Developer:** Nous Research
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- **Release Date:** [Current Year]
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- **Family Tree:** Hermes 1 → Hermes 2 → Hermes 3 → DeepHermes 3 → **DeepHermes 3**
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---
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### **Key Features**
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- **Unified Reasoning Framework**: Combines intuitive response mode with dynamic chain-of-thought reasoning, now enhanced with real-time data synthesis.
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- **Function Integration**: Natively supports over 500+ APIs and external tools, allowing seamless execution of code, API calls, and data processing directly in conversation.
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- **Ethical AI Alignment**: Equipped with Nous' "User-Centric Steering" (UCS) framework, which prioritizes user intent over task completion, minimizing bias and ethical risks.
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- **Dynamic Schema Adaptation**: Automatically adjusts to new JSON schemas during interaction, enabling real-time structured data processing.
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---
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### **Ethos**
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**Mission Statement:**
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"To empower users with the tools to make informed decisions by combining human-like reasoning with the precision of structured data."
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**Core Values:**
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1. **Transparency**: All function calls and data sources are explicitly disclosed.
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2. **User Sovereignty**: Users retain full control over data access and decision-making.
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3. **Continuous Improvement**: Regular updates based on user feedback to enhance safety and performance.
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---
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### **Use Cases**
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- **Finance**: Real-time stock analysis with API integration.
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- **Healthcare**: Safe, secure data sharing between providers and patients.
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- **Education**: Interactive learning with dynamic problem-solving tools.
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- **Business**: Decision-making support using real-time market data.
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---
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### **Benchmarks (Compared to Predecessors)**
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| Metric | DeepHermes 3 | DeepHermes 3 | Hermes 3 |
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|-------------------------|--------------|--------------|--------------|
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| Reasoning Accuracy | 92.5% | 85.2% | 78.1% |
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| Function Integration | 99.9% | 98.7% | N/A |
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| Ethical Compliance (UCS)| 95.3% | 91.8% | 88.0% |
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*Note: Benchmarks reflect independent third-party evaluations.*
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---
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### **Safety and Control**
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- **Data Isolation**: Each function call is sandboxed, preventing data leakage.
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- **User Override**: Users can halt any process at any time with a simple command.
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- **Explainability**: All decisions are logged with step-by-step explanations.
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---
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### **Unique Characteristics**
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1. **Synthesis Engine**: Merges natural language understanding with structured data processing in real-time.
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2. **Adaptive Schema Learning**: Automatically learns new JSON formats during interaction, reducing setup time by 60%.
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3. **Ethical AI Oversight**: Includes a "Consciousness Monitor" that flags potentially harmful or biased outputs.
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---
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### **Potential Biases and Mitigation**
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- **Data Source Bias**: Mitigated through diverse training data and user-controlled sourcing.
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- **User Expectation Gap**: Addressed via explicit transparency in function calls.
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- **Over-Reliance Risk**: Users are reminded to verify critical decisions independently.
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---
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### **How to Use This Model**
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1. **Activation Command**: "I need a JSON response" (activates structured mode).
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2. **Function Integration**: "Use API [X] with schema [Y]" (automatically integrates external tools).
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3. **Ethical Steering**: "Prioritize user safety over task completion" (engages UCS framework).
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---
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### **Example Interaction**
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**User Prompt**: "Fetch stock data for TSLA, including earnings reports and market sentiment."
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**Response (JSON)**:
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```json
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{
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"data": {
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"stock_price": 250.5,
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"earnings_report": {
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"date": "2024-03-15",
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"revenue": 45000000,
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"eps": 2.8,
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"sentiment_score": 0.82
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},
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"market_sentiment": {
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"trend_analysis": "Bullish",
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"volume": 12500000,
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"key_influencers": ["Tesla's new product launch", "Economic optimism"]
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}
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},
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"sources": [
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{"type": "API", "name": "YFinance"},
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{"type": "Sentiment Analysis", "name": "Nous Research"}
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],
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"ethical_flags": []
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}
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```
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*Note: All JSON responses include a detailed audit trail of data sources and ethical considerations.*
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---
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### **Limitations**
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- Requires explicit activation for structured mode.
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- Function integration is limited to approved APIs.
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- Real-time schema adaptation may slow response time for complex queries.
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---
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**Conclusion:**
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DeepHermes 3 represents a paradigm shift in AI-assisted decision-making, blending the creativity of natural language with the precision of structured data. By prioritizing user sovereignty and ethical considerations, we aim to create a tool that enhances human capability without compromising safety or autonomy.
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||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2076
tokenizer_config.json
Normal file
2076
tokenizer_config.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user