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DeepSeek V2 by deepseek-ai

 »  All LLMs  »  deepseek-ai  »  DeepSeek V2   URL Share it on

  7374   
  Arxiv:2311.18743   Arxiv:2405.04434   Autotrain compatible   Conversational   Custom code   Deepseek v2   Endpoints compatible   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/deepseek-ai/DeepSeek-V2 

DeepSeek V2 Benchmarks

LLME Score: 0.27704
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
DeepSeek V2 (deepseek-ai/DeepSeek-V2)

DeepSeek V2 Parameters and Internals

Model Type 
Mixture-of-Experts, Language Model
Use Cases 
Areas:
Research, Commercial Applications, Chatbots
Applications:
Language Understanding, Code Generation, Translation, Economical AI Applications
Primary Use Cases:
Text Generation, Conversation AI, Code Classification
Limitations:
Reduced performance on low resource languages and contexts, Complex and high resource computations
Considerations:
Utilize on recommended hardware for efficiency.
Additional Notes 
The model focuses on efficiency with a large parameter architecture for high performance.
Supported Languages 
English (Advanced), Chinese (Advanced), Code (Intermediate)
Training Details 
Data Sources:
High-quality corpus
Data Volume:
8.1 trillion tokens
Methodology:
Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL)
Context Length:
128000
Model Architecture:
Multi-head Latent Attention and DeepSeekMoE architecture
Safety Evaluation 
Methodologies:
Benchmarks, Comparison Tests, Open-ended Evaluation
Findings:
Effective performance on both language and coding benchmarks
Risk Categories:
Fairness, Bias, Misinformation
Ethical Considerations:
Contains Responsible AI guidelines
Responsible Ai Considerations 
Fairness:
Benchmarks evaluate across languages and use cases.
Transparency:
Performance and architecture details publicly shared.
Accountability:
DeepSeek-AI is accountable for model's outputs.
Mitigation Strategies:
Regular updates and evaluation on fairness and bias.
Input Output 
Input Format:
Supports text input, prompts for chat
Accepted Modalities:
text
Output Format:
Generated text with coherent structure
Performance Tips:
Use multipliers and optimization libraries for GPU.
Release Notes 
Version:
V2
Date:
2024
Notes:
Introduction of Mixture-of-Experts, Enhanced efficiency and reduced training costs.
LLM NameDeepSeek V2
Repository 🤗https://huggingface.co/deepseek-ai/DeepSeek-V2 
Model Size235.7b
Required VRAM378.4 GB
Updated2025-01-20
Maintainerdeepseek-ai
Model Typedeepseek_v2
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Model ArchitectureDeepseekV2ForCausalLM
Licenseother
Context Length163840
Model Max Length163840
Transformers Version4.39.3
Vocabulary Size102400
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than deepseek-ai/DeepSeek-V2.

Rank the DeepSeek V2 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241227
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