Qwen2.5 0.5B Instruct Gensyn Swarm Mammalian Lithe Barracuda by Agoboy

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Qwen2.5 0.5B Instruct Gensyn Swarm Mammalian Lithe Barracuda is an open-source language model by Agoboy. Features: 0.5b LLM, VRAM: 2GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.19.

  Arxiv:2402.03300   Autotrain compatible Base model:finetune:gensyn/qwe... Base model:gensyn/qwen2.5-0.5b...   Conversational   Endpoints compatible   Generated from trainer   Gensyn   Grpo   I am mammalian lithe barracuda   Instruct   Qwen2   Region:us   Rl-swarm   Safetensors   Trl

Qwen2.5 0.5B Instruct Gensyn Swarm Mammalian Lithe Barracuda Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 0.5B Instruct Gensyn Swarm Mammalian Lithe Barracuda (Agoboy/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-mammalian_lithe_barracuda)
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Qwen2.5 0.5B Instruct Gensyn Swarm Mammalian Lithe Barracuda Parameters and Internals

LLM NameQwen2.5 0.5B Instruct Gensyn Swarm Mammalian Lithe Barracuda
Repository ๐Ÿค—https://huggingface.co/Agoboy/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-mammalian_lithe_barracuda 
Model NameQwen2.5-0.5B-Instruct-Gensyn-Swarm-mammalian_lithe_barracuda
Base Model(s)  Gensyn/Qwen2.5-0.5B-Instruct   Gensyn/Qwen2.5-0.5B-Instruct
Model Size0.5b
Required VRAM2 GB
Updated2025-09-23
MaintainerAgoboy
Model Typeqwen2
Instruction-BasedYes
Model Files  2.0 GB   0.0 GB
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.50.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Agoboy/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-mammalian_lithe_barracuda.

Rank the Qwen2.5 0.5B Instruct Gensyn Swarm Mammalian Lithe Barracuda 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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Release v20260328a