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README.md
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license: apache-2.0
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---
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license: apache-2.0
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---
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# Helion-2.5-Rnd
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**DeepXR/Helion-2.5-Rnd** - Advanced Research & Development Language Model
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## Overview
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Helion-2.5-Rnd is a cutting-edge research language model designed for exceptional performance across multiple domains including:
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- **Advanced Reasoning**: Complex problem-solving and logical deduction
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- **Code Generation**: Multi-language programming assistance
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- **Mathematical Computation**: Proof generation and symbolic mathematics
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- **Multilingual Understanding**: 50+ languages with cultural context
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- **Creative Writing**: Story generation, poetry, and content creation
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- **Scientific Analysis**: Research paper understanding and synthesis
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- **Long Context**: Up to 131K tokens of context window
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## Model Architecture
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- **Type**: Transformer-based causal language model
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- **Parameters**: 70B+ parameters
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- **Architecture**: LLaMA-based with YARN positional embeddings
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- **Context Window**: 131,072 tokens (128K)
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- **Precision**: BF16/FP16 with INT8/INT4 quantization support
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- **Training Data**: 2.5 trillion tokens across diverse domains
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## Quick Start
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### Installation
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```bash
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# Clone the repository
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git clone https://huggingface.co/DeepXR/Helion-2.5-Rnd
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cd Helion-2.5-Rnd
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# Install dependencies
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pip install -r requirements.txt
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# Or use Docker
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docker build -t helion:2.5-rnd .
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```
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### Running the Server
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#### Using Python
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```bash
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python -m inference.server \
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--model /path/to/model \
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--tensor-parallel-size 2 \
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--max-model-len 131072 \
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--gpu-memory-utilization 0.95
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```
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#### Using Docker
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```bash
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docker run -d \
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--gpus all \
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-p 8000:8000 \
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-v /path/to/model:/models/helion \
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-e MODEL_PATH=/models/helion \
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-e TENSOR_PARALLEL_SIZE=2 \
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helion:2.5-rnd
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```
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### Using the Client
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```python
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from inference.client import HelionClient, HelionAssistant
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# Basic client
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client = HelionClient(base_url="http://localhost:8000")
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# Simple completion
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response = client.complete(
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"Explain quantum entanglement:",
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temperature=0.7,
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max_tokens=500
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)
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# Chat interface
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messages = [
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{"role": "system", "content": "You are a helpful AI assistant."},
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{"role": "user", "content": "What is machine learning?"}
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]
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response = client.chat(messages=messages)
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# High-level assistant
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assistant = HelionAssistant()
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response = assistant.chat("Write a Python function for quicksort")
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```
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## API Endpoints
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### Chat Completions
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```bash
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curl -X POST http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "DeepXR/Helion-2.5-Rnd",
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"messages": [
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{"role": "user", "content": "Hello, how are you?"}
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],
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"temperature": 0.7,
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"max_tokens": 1000
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}'
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```
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### Text Completions
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```bash
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curl -X POST http://localhost:8000/v1/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "DeepXR/Helion-2.5-Rnd",
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"prompt": "Once upon a time",
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"temperature": 0.8,
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"max_tokens": 500
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}'
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```
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### Health Check
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```bash
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curl http://localhost:8000/health
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```
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## Configuration
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### Model Parameters
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See `model_config.yaml` for full configuration options:
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- **Temperature**: 0.0-2.0 (default: 0.7)
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- **Top-p**: 0.0-1.0 (default: 0.9)
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- **Top-k**: Integer (default: 50)
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- **Max Tokens**: 1-131072 (default: 4096)
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- **Repetition Penalty**: 1.0-2.0 (default: 1.1)
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### Hardware Requirements
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**Minimum**:
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- 2x NVIDIA A100 80GB GPUs
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- 256GB RAM
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- 500GB NVMe SSD
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**Recommended**:
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- 4x NVIDIA H100 80GB GPUs
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- 512GB RAM
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- 1TB NVMe SSD
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## Capabilities
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### Code Generation
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```python
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messages = [
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{"role": "user", "content": "Write a binary search tree implementation in Rust"}
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]
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response = client.chat(messages=messages, temperature=0.3)
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```
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### Mathematical Reasoning
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```python
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response = client.complete(
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"Prove that the square root of 2 is irrational using contradiction:",
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temperature=0.5
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)
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```
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### Creative Writing
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```python
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response = client.complete(
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"Write a haiku about artificial intelligence:",
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temperature=0.9
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)
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```
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### Multilingual Support
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Helion supports 50+ languages including:
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- English, Spanish, French, German, Italian
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- Chinese (Simplified & Traditional), Japanese, Korean
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- Arabic, Hebrew, Hindi, Russian
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- And many more...
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## Benchmarks
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| Benchmark | Score |
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|-----------|-------|
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| MMLU | 84.7% |
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| GSM8K | 89.2% |
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| HumanEval | 75.6% |
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| MBPP | 72.3% |
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| ARC Challenge | 83.4% |
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| HellaSwag | 88.9% |
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| TruthfulQA | 61.2% |
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## Safety and Limitations
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### Safety Features
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- Content filtering for harmful outputs
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- PII (Personally Identifiable Information) detection
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- Prompt injection protection
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- Toxicity thresholds
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### Known Limitations
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- This is a **research model** - outputs should be verified
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- May exhibit biases present in training data
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- Performance on highly specialized domains may vary
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- Long context (>64K tokens) performance degrades
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- Not suitable for production without further fine-tuning
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## Research Use
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This model is intended for **research and development purposes**. It represents an experimental version of the Helion architecture and is continuously being improved.
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### Citation
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If you use this model in your research, please cite:
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```bibtex
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@misc{helion-2.5-rnd,
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title={Helion-2.5-Rnd: Advanced Research Language Model},
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author={DeepXR Team},
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year={2025},
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publisher={DeepXR},
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url={https://huggingface.co/DeepXR/Helion-2.5-Rnd}
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}
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```
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## License
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This model is released under the **Apache License 2.0**. See [LICENSE](LICENSE) for full details.
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## Support
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- **Documentation**: See `docs/` directory
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- **Issues**: Report on GitHub Issues
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- **Community**: Join our Discord/Slack
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- **Email**: support@deepxr.ai
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## Acknowledgments
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Built upon the excellent work of:
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- Meta AI (LLaMA architecture)
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- Hugging Face (Transformers library)
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- vLLM team (High-performance inference)
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- The open-source AI community
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---
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**DeepXR** - Advancing AI Research
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Version: 2.5.0-rnd | Status: Research | Updated: 2025-01-30
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