| { |
| "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": "float16", |
| "weight_format": "safetensors", |
| "total_shards": 83, |
| "shard_naming": "shard_00 through shard_82", |
| "shard_size_gb": 1.69, |
| "shard_size_gib": 1.57, |
| "total_size_gb": 140.27, |
| "total_size_gib": 130.71, |
| "size_note": "File managers show 1.57GiB (binary), imports show 1.69GB (decimal)", |
| "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": 83, |
| "pattern": "shard_{:02d}.safetensors", |
| "shard_range": "shard_00.safetensors to shard_82.safetensors", |
| "shard_size_gb": 1.69, |
| "shard_size_gib": 1.57, |
| "total_size_gb": 140.27, |
| "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": "support@deepxr.ai", |
| "research_email": "research@deepxr.ai", |
| "security_email": "security@deepxr.ai", |
| "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" |
| ] |
| } |
| ] |
| } |
