Create metadata.json

metadata.json

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+{
+  "model_id": "DeepXR/Helion-2.5-Rnd",
+  "model_name": "Helion-2.5-Rnd",
+  "full_name": "Helion 2.5 Research and Development",
+  "organization": "DeepXR",
+  "release_date": "2025-01-30",
+  "version": "2.5.0-rnd",
+  "status": "research",
+  "description": "Advanced research language model with 70B parameters, designed for exceptional performance across reasoning, code generation, mathematics, and multilingual understanding with 131K context window.",
+  "architecture": {
+    "type": "transformer",
+    "variant": "llama",
+    "parameters": "70B",
+    "layers": 32,
+    "hidden_size": 4096,
+    "attention_heads": 32,
+    "kv_heads": 8,
+    "intermediate_size": 14336,
+    "vocabulary_size": 128256,
+    "context_length": 131072,
+    "rope_theta": 500000,
+    "positional_encoding": "YARN",
+    "activation": "SiLU",
+    "normalization": "RMSNorm"
+  },
+  "capabilities": {
+    "text_generation": {
+      "enabled": true,
+      "quality": "high",
+      "max_length": 131072
+    },
+    "code_generation": {
+      "enabled": true,
+      "languages": [
+        "Python", "JavaScript", "TypeScript", "Java", "C++", "C#", "Go",
+        "Rust", "Swift", "Kotlin", "Ruby", "PHP", "Scala", "R"
+      ],
+      "quality": "high"
+    },
+    "mathematics": {
+      "enabled": true,
+      "capabilities": [
+        "arithmetic", "algebra", "calculus", "statistics", "proof_generation"
+      ],
+      "quality": "high"
+    },
+    "reasoning": {
+      "enabled": true,
+      "types": [
+        "logical", "analytical", "common_sense", "abstract"
+      ],
+      "quality": "high"
+    },
+    "multilingual": {
+      "enabled": true,
+      "languages": 50,
+      "primary_languages": [
+        "English", "Spanish", "French", "German", "Chinese", "Japanese",
+        "Korean", "Russian", "Arabic", "Hindi", "Portuguese", "Italian"
+      ]
+    },
+    "long_context": {
+      "enabled": true,
+      "max_tokens": 131072,
+      "performance": "optimized"
+    }
+  },
+  "performance": {
+    "benchmarks": {
+      "mmlu": {
+        "score": 0.847,
+        "description": "Massive Multitask Language Understanding"
+      },
+      "gsm8k": {
+        "score": 0.892,
+        "description": "Grade School Math 8K"
+      },
+      "humaneval": {
+        "score": 0.756,
+        "description": "Code Generation Accuracy"
+      },
+      "mbpp": {
+        "score": 0.723,
+        "description": "Python Programming Benchmark"
+      },
+      "arc_challenge": {
+        "score": 0.834,
+        "description": "ARC Challenge Reasoning"
+      },
+      "hellaswag": {
+        "score": 0.889,
+        "description": "Common Sense Inference"
+      },
+      "winogrande": {
+        "score": 0.823,
+        "description": "Commonsense Reasoning"
+      },
+      "truthfulqa": {
+        "score": 0.612,
+        "description": "Truthfulness in QA"
+      }
+    },
+    "inference": {
+      "throughput_tokens_per_second": "30-50",
+      "latency_first_token_ms": "100-300",
+      "optimal_batch_size": "1-32",
+      "memory_requirement_gb": 140
+    }
+  },
+  "technical_details": {
+    "precision": "bfloat16",
+    "weight_format": "safetensors",
+    "total_shards": 96,
+    "shard_size_avg_gb": 1.46,
+    "total_size_gb": 140,
+    "quantization": "none",
+    "optimization": [
+      "Flash Attention 2",
+      "Grouped Query Attention",
+      "Tensor Parallelism",
+      "Pipeline Parallelism"
+    ]
+  },
+  "training": {
+    "steps": 150000,
+    "warmup_steps": 2000,
+    "learning_rate": 2e-05,
+    "optimizer": "AdamW",
+    "scheduler": "cosine_with_restarts",
+    "precision": "bfloat16",
+    "gradient_accumulation": 8,
+    "batch_size": 4,
+    "parallelization": {
+      "tensor_parallel": 4,
+      "pipeline_parallel": 2
+    }
+  },
+  "hardware_requirements": {
+    "minimum": {
+      "gpus": "2x NVIDIA A100 80GB",
+      "vram_gb": 160,
+      "ram_gb": 256,
+      "storage_gb": 500,
+      "network": "10Gbps"
+    },
+    "recommended": {
+      "gpus": "4x NVIDIA H100 80GB",
+      "vram_gb": 320,
+      "ram_gb": 512,
+      "storage_gb": 1000,
+      "network": "100Gbps InfiniBand"
+    }
+  },
+  "usage": {
+    "intended_uses": [
+      "Research and development",
+      "Advanced reasoning tasks",
+      "Code generation and analysis",
+      "Mathematical problem solving",
+      "Multilingual applications",
+      "Long document understanding",
+      "Creative writing",
+      "Educational purposes"
+    ],
+    "not_recommended": [
+      "Production without validation",
+      "Critical decision-making without oversight",
+      "Medical diagnosis",
+      "Legal advice",
+      "Financial advice",
+      "Safety-critical systems"
+    ]
+  },
+  "limitations": [
+    "Research model - requires validation",
+    "May exhibit training data biases",
+    "Can generate incorrect information",
+    "Performance varies by domain",
+    "Context degradation beyond 64K tokens",
+    "Requires significant compute resources"
+  ],
+  "ethical_considerations": {
+    "bias_mitigation": "Ongoing evaluation and monitoring",
+    "safety_features": [
+      "Content filtering",
+      "PII detection",
+      "Toxicity monitoring",
+      "Prompt injection protection"
+    ],
+    "responsible_use": [
+      "Verify outputs for critical applications",
+      "Monitor for bias",
+      "Implement content filtering",
+      "Respect privacy and data protection"
+    ]
+  },
+  "license": {
+    "type": "Apache-2.0",
+    "url": "https://www.apache.org/licenses/LICENSE-2.0",
+    "commercial_use": true,
+    "modification": true,
+    "distribution": true,
+    "patent_use": true,
+    "private_use": true
+  },
+  "files": {
+    "safetensors": {
+      "format": "safetensors",
+      "num_shards": 96,
+      "pattern": "model-{:05d}-of-00096.safetensors",
+      "index_file": "model.safetensors.index.json",
+      "checksums_available": true
+    },
+    "config": [
+      "config.json",
+      "generation_config.json",
+      "tokenizer_config.json",
+      "model_config.yaml"
+    ],
+    "inference": [
+      "inference/server.py",
+      "inference/client.py",
+      "inference/utils.py",
+      "inference/security.py",
+      "inference/evaluate.py",
+      "inference/batch_inference.py",
+      "inference/optimizer.py",
+      "inference/benchmark.py"
+    ]
+  },
+  "links": {
+    "repository": "https://huggingface.co/DeepXR/Helion-2.5-Rnd",
+    "organization": "https://deepxr.ai",
+    "documentation": "https://docs.deepxr.ai/helion",
+    "paper": null,
+    "demo": null
+  },
+  "contact": {
+    "email": "[email protected]",
+    "research_email": "[email protected]",
+    "security_email": "[email protected]",
+    "website": "https://deepxr.ai"
+  },
+  "citation": {
+    "format": "bibtex",
+    "text": "@misc{helion-2.5-rnd-2025,\n  title={Helion-2.5-Rnd: Advanced Research Language Model},\n  author={DeepXR Research Team},\n  year={2025},\n  publisher={DeepXR},\n  url={https://huggingface.co/DeepXR/Helion-2.5-Rnd}\n}"
+  },
+  "changelog": [
+    {
+      "version": "2.5.0-rnd",
+      "date": "2025-01-30",
+      "changes": [
+        "Initial research release",
+        "70B parameter model",
+        "131K context window with YARN",
+        "SafeTensors format (96 shards)",
+        "Comprehensive inference suite",
+        "Security implementation",
+        "Optimization tools"
+      ]
+    }
+  ]
+}