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Qwen2.5 0.5B Mask Uni30 Edu Instruct 3 by NaoS2

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Qwen2.5 0.5B Mask Uni30 Edu Instruct 3 is an open-source language model by NaoS2. Features: 0.5b LLM, VRAM: 2GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.17.

  Arxiv:1910.09700   Autotrain compatible   Conversational   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sft   Trl
Model Card on HF 🤗: https://huggingface.co/NaoS2/qwen2.5-0.5B_mask_uni30_edu_instruct-3 

Qwen2.5 0.5B Mask Uni30 Edu Instruct 3 Benchmarks

LLME Score: 0.173
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 Mask Uni30 Edu Instruct 3 (NaoS2/qwen2.5-0.5B_mask_uni30_edu_instruct-3)
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Qwen2.5 0.5B Mask Uni30 Edu Instruct 3 Parameters and Internals

LLM NameQwen2.5 0.5B Mask Uni30 Edu Instruct 3
Repository 🤗https://huggingface.co/NaoS2/qwen2.5-0.5B_mask_uni30_edu_instruct-3 
Model Size0.5b
Required VRAM2 GB
Updated2025-09-23
MaintainerNaoS2
Model Typeqwen2
Instruction-BasedYes
Model Files  2.0 GB
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.47.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

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Qwen2.5 0.5B Instruct32K / 1 GB6089483505
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Note: green Score (e.g. "73.2") means that the model is better than NaoS2/qwen2.5-0.5B_mask_uni30_edu_instruct-3.

Rank the Qwen2.5 0.5B Mask Uni30 Edu Instruct 3 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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