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MedCore Qwen2.5 0.5B 16bit Mini by MatthewsFace

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MedCore Qwen2.5 0.5B 16bit Mini is an open-source language model by MatthewsFace. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.18.

  16bit   Autotrain compatible Base model:finetune:matthewsfa... Base model:matthewsface/qwen2....   Conversational   En   Endpoints compatible   Instruct   Pytorch   Quantized   Qwen2   Region:us   Sft   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/MatthewsFace/MedCore-Qwen2.5-0.5B_16bit-Mini 

MedCore Qwen2.5 0.5B 16bit Mini Benchmarks

LLME Score: 0.18309
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MedCore Qwen2.5 0.5B 16bit Mini (MatthewsFace/MedCore-Qwen2.5-0.5B_16bit-Mini)
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MedCore Qwen2.5 0.5B 16bit Mini Parameters and Internals

LLM NameMedCore Qwen2.5 0.5B 16bit Mini
Repository 🤗https://huggingface.co/MatthewsFace/MedCore-Qwen2.5-0.5B_16bit-Mini 
Base Model(s)  MatthewsFace/Qwen2.5-0.5B-Instruct   MatthewsFace/Qwen2.5-0.5B-Instruct
Model Size0.5b
Required VRAM1 GB
Updated2025-03-20
MaintainerMatthewsFace
Model Typeqwen2
Instruction-BasedYes
Model Files  1.0 GB
Supported Languagesen
Quantization Type16bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.48.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than MatthewsFace/MedCore-Qwen2.5-0.5B_16bit-Mini.

Rank the MedCore Qwen2.5 0.5B 16bit Mini 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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