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DeepSeek Coder V2 Lite Base AWQ by TechxGenus

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DeepSeek Coder V2 Lite Base AWQ is an open-source language model by TechxGenus. Features: 2.6b LLM, VRAM: 9.1GB, Context: 160K, License: other, Quantized, Code Generating, LLM Explorer Score: 0.16.

  Arxiv:2401.06066   4-bit   Autotrain compatible   Awq   Codegen   Conversational   Custom code   Deepseek v2   Endpoints compatible   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TechxGenus/DeepSeek-Coder-V2-Lite-Base-AWQ 

DeepSeek Coder V2 Lite Base AWQ Benchmarks

LLME Score: 0.15953
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
DeepSeek Coder V2 Lite Base AWQ (TechxGenus/DeepSeek-Coder-V2-Lite-Base-AWQ)
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DeepSeek Coder V2 Lite Base AWQ Parameters and Internals

Model Type 
Code language model, Mixture-of-Experts (MoE)
Supported Languages 
total (; languages_proficiency:{)
Training Details 
Data Sources:
Multi-source high-quality corpus
Data Volume:
6 trillion tokens
Methodology:
Mixture-of-Experts (MoE) approach
Context Length:
128000
Hardware Used:
80GB*8 GPUs
Input Output 
Input Format:
Text input for code completion, chat completion.
Accepted Modalities:
text
Output Format:
Generated code or chat responses.
LLM NameDeepSeek Coder V2 Lite Base AWQ
Repository 🤗https://huggingface.co/TechxGenus/DeepSeek-Coder-V2-Lite-Base-AWQ 
Model Size2.6b
Required VRAM9.1 GB
Updated2025-10-14
MaintainerTechxGenus
Model Typedeepseek_v2
Model Files  5.0 GB: 1-of-2   4.1 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Generates CodeYes
Model ArchitectureDeepseekV2ForCausalLM
Licenseother
Context Length163840
Model Max Length163840
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Padding Token<｜end▁of▁sentence｜>
Vocabulary Size102400
Torch Data Typefloat16

Best Alternatives to DeepSeek Coder V2 Lite Base AWQ

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...eek Coder V2 Lite Instruct AWQ160K / 9.1 GB27857
Note: green Score (e.g. "73.2") means that the model is better than TechxGenus/DeepSeek-Coder-V2-Lite-Base-AWQ.

Rank the DeepSeek Coder V2 Lite Base AWQ Capabilities

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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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