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WiNGPT Babel by winninghealth

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Base model:quantized:qwen/qwen...   Base model:qwen/qwen2.5-1.5b   Conversational   En   Endpoints compatible   Gguf   Multilingual   Q4   Quantized   Qwen2   Region:us   Safetensors   Translation   Zh
Model Card on HF 🤗: https://huggingface.co/winninghealth/WiNGPT-Babel 

WiNGPT Babel Benchmarks

LLME Score: 0.24217
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
WiNGPT Babel (winninghealth/WiNGPT-Babel)
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WiNGPT Babel Parameters and Internals

LLM NameWiNGPT Babel
Repository 🤗https://huggingface.co/winninghealth/WiNGPT-Babel 
Base Model(s)  Qwen/Qwen2.5-1.5B   Qwen/Qwen2.5-1.5B
Model Size1.5b
Required VRAM1 GB
Updated2025-07-19
Maintainerwinninghealth
Model Typeqwen2
Model Files  1.0 GB   1.1 GB   1.6 GB   3.1 GB
Supported Languagesen zh
GGUF QuantizationYes
Quantization Typeq4|gguf|q4_k|q5_k
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.43.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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...ill Qwen 1.5B Unsloth Bnb 4bit128K / 1.8 GB834716
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... R1 Distill Qwen 1.5B Bnb 4bit128K / 1.6 GB218911
DeepSeek R1 ForumNXT128K / 3.5 GB50
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Note: green Score (e.g. "73.2") means that the model is better than winninghealth/WiNGPT-Babel.

Rank the WiNGPT Babel 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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Release v20241124
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