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Test by yitao416

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  Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2-0.5b-ins...   Conversational   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/yitao416/test 

Test Benchmarks

LLME Score: 0.19099
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Test (yitao416/test)

Test Parameters and Internals

Model Type 
text-generation-inference, transformers, unsloth, qwen2, trl
Additional Notes 
This Qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameTest
Repository 🤗https://huggingface.co/yitao416/test 
Base Model(s)  Qwen/Qwen2-0.5B-Instruct   Qwen/Qwen2-0.5B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2025-02-22
Maintaineryitao416
Model Typeqwen2
Instruction-BasedYes
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4   3.1 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.42.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Test

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B Instruct 1M986K / 15.4 GB289038236
Qwen2.5 7B RRP 1M986K / 15.2 GB2944
Qwen2.5 7B CelestialHarmony 1M986K / 14.8 GB1535
COCO 7B Instruct 1M986K / 15.2 GB1059
Q2.5 Instruct 1M Harmony986K / 15.2 GB611
Impish QWEN 7B 1M986K / 15.2 GB701
Qwen2.5 7B DeepSeek R1 1M986K / 15.2 GB8810
Qwen2.5 7B Sky R1 Mini986K / 15.2 GB250
Qwen2.5 7B Instruct 1M986K / 15.2 GB6332
MwM 7B CoT Merge1986K / 15.2 GB432
Note: green Score (e.g. "73.2") means that the model is better than yitao416/test.

Rank the Test 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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