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LeoPARD Coder 0.5.5 by VortexHunter23

 »  All LLMs  »  VortexHunter23  »  LeoPARD Coder 0.5.5   URL Share it on

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LeoPARD Coder 0.5.5 is an open-source language model by VortexHunter23. Features: 8.4b LLM, VRAM: 9.9GB, Context: 128K, License: apache-2.0, Code Generating, LLM Explorer Score: 0.2.

  4-bit   Autotrain compatible Base model:quantized:vortexhun... Base model:vortexhunter23/leop...   Bitsandbytes   Codegen   Conversational   En   Endpoints compatible   Qwen2   Region:us   Safetensors   Sft   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/VortexHunter23/LeoPARD-Coder-0.5.5 

LeoPARD Coder 0.5.5 Benchmarks

LLME Score: 0.19607
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LeoPARD Coder 0.5.5 (VortexHunter23/LeoPARD-Coder-0.5.5)
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LeoPARD Coder 0.5.5 Parameters and Internals

LLM NameLeoPARD Coder 0.5.5
Repository 🤗https://huggingface.co/VortexHunter23/LeoPARD-Coder-0.5.5 
Base Model(s)  VortexHunter23/LeoPARD-Coder-0.5   VortexHunter23/LeoPARD-Coder-0.5
Model Size8.4b
Required VRAM9.9 GB
Updated2025-09-23
MaintainerVortexHunter23
Model Typeqwen2
Model Files  5.0 GB: 1-of-2   4.9 GB: 2-of-2
Supported Languagesen
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.51.3
Tokenizer ClassLlamaTokenizerFast
Padding Token<|vision_pad|>
Vocabulary Size152064
Torch Data Typebfloat16

Best Alternatives to LeoPARD Coder 0.5.5

Best Alternatives
Context / RAM
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Likes
LeoPARD Coder 0.8128K / 9.9 GB60
LeoPARD Coder 0.7.4128K / 9.9 GB60
LeoPARD Coder 0.6128K / 9.9 GB50
LeoPARD Coder 0.7128K / 9.9 GB50
LeoPARD Coder 0.5.9128K / 9.9 GB60
LeoPARD Coder 0.5128K / 9.9 GB60
LeoPARD Coder 0.4128K / 9.9 GB50
LeoPARD Coder 0.2128K / 9.9 GB70
Shed Coder 0.5128K / 9.9 GB70
Shed Coder 0.4128K / 9.9 GB70
Note: green Score (e.g. "73.2") means that the model is better than VortexHunter23/LeoPARD-Coder-0.5.5.

Rank the LeoPARD Coder 0.5.5 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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