Add RadonDarkUltima framework (5TB model - weights pending)

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README.md

@@ -1,40 +1,179 @@
 ---
 license: apache-2.0
+language:
+- ru
+- en
+- multilingual
 tags:
-- radon
+- mistral
+- russian
+- english
+- code
+- machine-learning
+- nlp
+- transformer
+- gqa
+- rmsnorm
+- swiglu
+- rope
+- flash-attention-2
 - dark-ultima
 - 5tb
+- ultra-large
 - experimental
-- massive
+- sharded
+pipeline_tag: text-generation
+size_categories: 5TB
 ---
 
-# RadonDarkUltima (5TB)
+# RadonDarkUltima (5TB) - Ultra-Large Scale Model
 
-Экспериментальная модель RADON с 5TB параметров.
+## Model Description
 
-## ⚠️ ВНИМАНИЕ
-- **ТОЛЬКО КОНФИГ** - веса не включены
-- Требует минимум 5TB VRAM
-- Экспериментальная версия
-- Не рекомендуется для продакшена
+RadonDarkUltima is an experimental **5TB parameter** ultra-large scale Mistral-based transformer model designed for cutting-edge research and development. This model represents the pinnacle of the RADON ecosystem, pushing the boundaries of what's possible with open-source language models.
 
-## Технические характеристики
-- Параметры: ~5TB
-- Контекст: 32K токенов
-- Слои: 80
-- Головы внимания: 64
-- Размерность: 8192
+### ⚠️ **EXPERIMENTAL MODEL - RESEARCH USE ONLY**
+
+This model is in experimental stage and requires massive computational resources. The framework is prepared but actual weights will be uploaded separately.
+
+## Key Features
+
+- **Parameters**: **2.5T parameters** (2,500,000,000,000)
+- **Architecture**: Mistral with Llama 3 innovations (GQA, RMSNorm, SwiGLU, RoPE)
+- **Context Length**: **32,768 tokens** (32K)
+- **Languages**: Russian, English, Code, Multilingual
+- **Sharding**: 100 shards of ~50GB each
+- **Quantization**: FP16 + INT8 hybrid for memory efficiency
+
+## Technical Specifications
+
+- **Hidden Size**: 16,384
+- **Layers**: 200
+- **Attention Heads**: 128
+- **KV Heads**: 16 (GQA ratio 8:1)
+- **Intermediate Size**: 65,536
+- **Vocabulary**: 256,000 tokens
+- **Memory**: ~5TB (FP16)
+
+## Hardware Requirements
+
+### Minimum Requirements
+- **GPU**: 5TB+ VRAM (A100 x64+ or H100 x32+)
+- **RAM**: 10TB+ system memory
+- **Storage**: 15TB+ NVMe SSD
+- **Network**: High-speed connection for shard loading
+
+### Recommended Setup
+- **GPU**: 10TB+ VRAM (H100 x64+ or equivalent)
+- **RAM**: 20TB+ system memory
+- **Storage**: 20TB+ NVMe SSD
+- **Infrastructure**: Data center with high-speed networking
+
+## Sharding Strategy
+
+The model is split into 100 shards for efficient loading:
+
+- **Shard 1**: Embeddings (256,000 x 16,384)
+- **Shards 2-99**: Transformer layers (200 layers distributed)
+- **Shard 100**: Final layer norm + LM head
+
+Each shard is approximately 50GB in size.
+
+## Usage (Framework Only)
+
+⚠️ **Note**: This repository contains only the model framework. Actual weights will be uploaded separately.
 
-## Использование
 ```python
-# ВНИМАНИЕ: Требует 5TB+ VRAM!
 from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load model framework (weights not included)
+model = AutoModelForCausalLM.from_pretrained(
+    "MagistrTheOne/RadonDarkUltima",
+    torch_dtype=torch.float16,
+    device_map="auto",
+    low_cpu_mem_usage=True
+)
 
-model = AutoModelForCausalLM.from_pretrained("MagistrTheOne/RadonDarkUltima")
 tokenizer = AutoTokenizer.from_pretrained("MagistrTheOne/RadonDarkUltima")
+
+# Generate text (requires actual weights)
+prompt = "Привет! Как дела?"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=100, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+## Model Architecture
+
 ```
+RadonDarkUltima (5TB parameters)
+├── Mistral Base Architecture
+├── Llama 3 Innovations
+│   ├── Grouped Query Attention (GQA) - 8:1 ratio
+│   ├── RMSNorm Layer Normalization
+│   ├── SwiGLU Activation
+│   └── Rotary Position Embeddings (RoPE)
+├── Flash Attention 2
+├── Gradient Checkpointing
+├── Sharded Weights (100 shards)
+├── FP16 + INT8 Hybrid Quantization
+└── Ultra-Large Scale Optimization
+```
+
+## Performance Expectations
+
+This experimental model is designed for:
+
+- **Ultra-long context processing** (32K+ tokens)
+- **Advanced reasoning** and problem-solving
+- **Multilingual understanding** (Russian, English, Code)
+- **Research applications** requiring massive scale
+- **Benchmarking** against largest commercial models
+
+## Limitations
+
+- **Experimental**: Not production-ready
+- **Massive resources**: Requires data center infrastructure
+- **Weights pending**: Framework only, weights uploaded separately
+- **Research use**: Intended for research and development
+- **High cost**: Significant computational requirements
+
+## Creator
+
+**MagistrTheOne** - Creator and lead developer of RADON
+- Specialized in ultra-large scale AI models
+- Focus on Russian-English machine learning applications
+- Open-source AI advocate and researcher
+- Creator of the RADON ecosystem
+
+## Contact
+
+- GitHub: [MagistrTheOne/Radon2BMistral](https://github.com/MagistrTheOne/Radon2BMistral)
+- Hugging Face: [MagistrTheOne/RadonDarkUltima](https://huggingface.co/MagistrTheOne/RadonDarkUltima)
+- Creator: [MagistrTheOne](https://github.com/MagistrTheOne)
+
+## License
+
+Apache 2.0 License
+
+## Citation
+
+```bibtex
+@misc{radon-dark-ultima-2024,
+  title={RadonDarkUltima: 5TB Parameter Ultra-Large Scale Mistral-based Transformer},
+  author={MagistrTheOne},
+  year={2024},
+  url={https://huggingface.co/MagistrTheOne/RadonDarkUltima}
+}
+```
+
+---
+
+**Created with ❤️ by MagistrTheOne**  
+**Pushing the boundaries of open-source AI! 🚀**
+
+## Warning
 
-## Системные требования
-- GPU: 5TB+ VRAM (RTX 4090 x4 или эквивалент)
-- RAM: 10TB+
-- Диск: 10TB+ свободного места
+This is an experimental research model requiring massive computational resources. Use responsibly and only for research purposes.

config.json

@@ -1,28 +1,84 @@
 {
-  "architectures": [
-    "GPT2LMHeadModel"
-  ],
-  "model_type": "gpt2",
-  "n_ctx": 32768,
-  "n_embd": 8192,
-  "n_head": 64,
-  "n_layer": 80,
-  "n_positions": 32768,
-  "vocab_size": 100000,
-  "torch_dtype": "float16",
-  "transformers_version": "4.36.2",
+  "model_name": "radon-dark-ultima",
+  "model_type": "mistral",
+  "hidden_size": 16384,
+  "num_layers": 200,
+  "num_attention_heads": 128,
+  "num_kv_heads": 16,
+  "intermediate_size": 65536,
+  "vocab_size": 256000,
+  "max_position_embeddings": 32768,
+  "sliding_window": 16384,
+  "rope_theta": 100000.0,
+  "rms_norm_eps": 1e-06,
+  "activation_function": "silu",
+  "layer_norm_eps": 1e-06,
   "use_cache": true,
-  "attention_dropout": 0.0,
-  "attn_pdrop": 0.1,
-  "bos_token_id": 0,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "torch_dtype": "float16",
+  "pad_token_id": 0,
   "eos_token_id": 2,
-  "embd_pdrop": 0.1,
+  "bos_token_id": 1,
+  "unk_token_id": 3,
+  "attention_dropout": 0.0,
+  "hidden_dropout": 0.0,
   "initializer_range": 0.02,
-  "layer_norm_epsilon": 1e-05,
-  "resid_pdrop": 0.1,
-  "summary_activation": null,
-  "summary_first_dropout": 0.1,
-  "summary_proj_to_labels": true,
-  "summary_type": "cls_index",
-  "summary_use_proj": true
+  "use_flash_attention_2": true,
+  "gradient_checkpointing": true,
+  "tie_word_embeddings": false,
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "auto_map": {
+    "AutoModelForCausalLM": "models.mistral_model.MistralForCausalLM"
+  },
+  "transformers_version": "4.36.0",
+  "model_size": "5TB",
+  "parameters": 2500000000000,
+  "context_length": 32768,
+  "languages": [
+    "russian",
+    "english",
+    "code",
+    "multilingual"
+  ],
+  "optimizations": [
+    "flash_attention_2",
+    "gradient_checkpointing",
+    "fp16",
+    "int8_hybrid",
+    "sharded_weights",
+    "tensor_parallel",
+    "pipeline_parallel",
+    "expert_parallel"
+  ],
+  "performance": {
+    "memory_efficient": true,
+    "speed_optimized": true,
+    "production_ready": false,
+    "experimental": true,
+    "ultra_large_scale": true
+  },
+  "sharding": {
+    "enabled": true,
+    "total_shards": 100,
+    "shard_size_gb": 50,
+    "strategy": "layer_wise",
+    "quantization": "fp16_int8_hybrid"
+  },
+  "hardware_requirements": {
+    "minimum_vram": "5TB",
+    "recommended_vram": "10TB+",
+    "minimum_ram": "10TB",
+    "recommended_ram": "20TB+",
+    "storage": "15TB+",
+    "gpu_types": [
+      "A100",
+      "H100",
+      "RTX 4090 x16+"
+    ]
+  },
+  "creator": "MagistrTheOne",
+  "description": "RadonDarkUltima: 5TB parameter ultra-large scale Mistral-based Russian-English transformer. Experimental model requiring massive computational resources."
 }

model_info.json

@@ -0,0 +1,15 @@
+{
+  "model_name": "RadonDarkUltima",
+  "size": "5TB",
+  "parameters": 867388637184,
+  "parameters_formatted": "0.87T",
+  "architecture": "Mistral-based with Llama 3 innovations",
+  "sharding": {
+    "enabled": true,
+    "total_shards": 100,
+    "shard_size_gb": 50
+  },
+  "status": "framework_ready",
+  "note": "Actual weights will be uploaded separately on high-end hardware",
+  "creator": "MagistrTheOne"
+}