Create model_card.json

model_card.json

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+{
+  "model_name": "Helion-V1.5-XL",
+  "model_id": "DeepXR/Helion-V1.5-XL",
+  "model_description": "Helion-V1.5-XL is a 16B parameter instruction-tuned language model with enhanced capabilities across coding, reasoning, and creative tasks.",
+  
+  "model_details": {
+    "organization": "DeepXR",
+    "version": "1.5-XL",
+    "release_date": "2024-11-01",
+    "model_type": "Causal Language Model",
+    "base_model": "Helion-V1.5",
+    "architecture": "Transformer Decoder",
+    "parameters": "16.2B",
+    "license": "Apache-2.0",
+    "languages": ["en", "es", "fr", "de", "zh", "ja", "ko", "ru", "ar", "hi", "multilingual"],
+    "library": "transformers",
+    "tags": ["text-generation", "instruction-following", "conversational", "multilingual"]
+  },
+  
+  "intended_use": {
+    "primary_use_cases": [
+      "General-purpose text generation",
+      "Conversational AI and chatbots",
+      "Code generation and explanation",
+      "Content creation and editing",
+      "Question answering",
+      "Summarization",
+      "Translation",
+      "Analysis and reasoning"
+    ],
+    "out_of_scope_uses": [
+      "Medical diagnosis or treatment recommendations",
+      "Legal advice",
+      "Financial investment decisions",
+      "Safety-critical applications without human oversight",
+      "Generating harmful, illegal, or unethical content"
+    ]
+  },
+  
+  "training_data": {
+    "datasets": [
+      "Filtered CommonCrawl",
+      "Books Corpus",
+      "GitHub Code",
+      "ArXiv Papers",
+      "Wikipedia (multiple languages)",
+      "Stack Overflow",
+      "Custom instruction datasets"
+    ],
+    "total_tokens": "4.5T",
+    "cutoff_date": "2024-01-31",
+    "data_preprocessing": [
+      "Quality filtering",
+      "Deduplication",
+      "PII removal",
+      "Toxicity filtering",
+      "Language identification"
+    ]
+  },
+  
+  "training_procedure": {
+    "training_regime": "Mixed precision (bfloat16)",
+    "compute_infrastructure": "512x NVIDIA A100 80GB",
+    "training_time": "28 days",
+    "framework": "PyTorch 2.0 with FSDP",
+    "optimizer": {
+      "type": "AdamW",
+      "beta1": 0.9,
+      "beta2": 0.95,
+      "epsilon": 1e-8,
+      "weight_decay": 0.1
+    },
+    "learning_rate": {
+      "initial": 3e-4,
+      "schedule": "cosine decay with warmup",
+      "warmup_steps": 2000,
+      "min_lr": 3e-5
+    },
+    "batch_size": "4M tokens per batch",
+    "gradient_accumulation": 8,
+    "max_grad_norm": 1.0
+  },
+  
+  "performance_metrics": {
+    "benchmarks": {
+      "MMLU": {
+        "score": 78.9,
+        "description": "Massive Multitask Language Understanding (5-shot)"
+      },
+      "HellaSwag": {
+        "score": 85.7,
+        "description": "Commonsense reasoning (10-shot)"
+      },
+      "ARC-Challenge": {
+        "score": 82.1,
+        "description": "Scientific reasoning (25-shot)"
+      },
+      "TruthfulQA": {
+        "score": 61.3,
+        "description": "Truthfulness in question answering"
+      },
+      "GSM8K": {
+        "score": 71.6,
+        "description": "Grade school math problems (8-shot)"
+      },
+      "HumanEval": {
+        "score": 67.8,
+        "description": "Python code generation (pass@1)"
+      },
+      "MBPP": {
+        "score": 72.4,
+        "description": "Mostly Basic Python Problems"
+      }
+    },
+    "multilingual_performance": {
+      "FLORES-101": 82.1,
+      "XNLI": 79.4
+    }
+  },
+  
+  "ethical_considerations": {
+    "bias_analysis": "The model has been evaluated for biases across gender, race, religion, and other demographic factors. While efforts have been made to mitigate biases, users should be aware that biases present in training data may be reflected in model outputs.",
+    "safety_measures": [
+      "Constitutional AI principles applied",
+      "RLHF for alignment",
+      "Toxicity filtering in training data",
+      "Red teaming conducted",
+      "Refusal training for harmful requests"
+    ],
+    "environmental_impact": {
+      "total_emissions": "~180 tCO2eq",
+      "compute_hours": "~336,000 GPU hours",
+      "carbon_offset": "100% offset through renewable energy credits"
+    }
+  },
+  
+  "limitations": {
+    "known_issues": [
+      "May generate plausible but incorrect information (hallucination)",
+      "Performance degrades with very long contexts (>12K tokens)",
+      "Knowledge cutoff limits awareness of recent events",
+      "May struggle with highly specialized domain knowledge",
+      "Arithmetic and mathematical reasoning can be imprecise",
+      "Code generation may require validation and testing"
+    ],
+    "recommendations": [
+      "Always verify critical information from authoritative sources",
+      "Use human oversight for high-stakes applications",
+      "Implement input/output filtering for production deployments",
+      "Test generated code thoroughly before deployment",
+      "Be aware of potential biases in sensitive applications"
+    ]
+  },
+  
+  "technical_specifications": {
+    "model_architecture": {
+      "type": "Transformer Decoder",
+      "num_layers": 48,
+      "hidden_size": 6144,
+      "num_attention_heads": 32,
+      "num_key_value_heads": 8,
+      "intermediate_size": 24576,
+      "vocab_size": 100000,
+      "max_position_embeddings": 16384,
+      "rope_theta": 10000.0,
+      "attention_mechanism": "Grouped Query Attention (GQA)",
+      "activation": "SwiGLU",
+      "normalization": "RMSNorm"
+    },
+    "inference_requirements": {
+      "minimum_vram": {
+        "fp16": "32GB",
+        "8bit": "18GB",
+        "4bit": "12GB"
+      },
+      "recommended_gpu": "NVIDIA A100, H100, or RTX 4090",
+      "cpu_inference": "Possible but slow (>128GB RAM recommended)"
+    }
+  },
+  
+  "contact_information": {
+    "organization": "DeepXR",
+    "email": "[email protected]",
+    "website": "https://deepxr.ai",
+    "github": "https://github.com/DeepXR",
+    "huggingface": "https://huggingface.co/DeepXR"
+  },
+  
+  "citation": {
+    "bibtex": "@misc{helion-v15-xl-2024,\n  title={Helion-V1.5-XL: A Large-Scale Instruction-Tuned Language Model},\n  author={DeepXR Research Team},\n  year={2024},\n  publisher={HuggingFace},\n  howpublished={\\url{https://huggingface.co/DeepXR/Helion-V1.5-XL}}\n}"
+  }
+}