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Xwen 7B Chat by xwen-team

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Xwen 7B Chat is an open-source language model by xwen-team. Features: 7b LLM, VRAM: 15.2GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.27.

  Arxiv:2406.11939   Arxiv:2412.15115 Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-7b   Conversational   En   Endpoints compatible   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Zh
Model Card on HF 🤗: https://huggingface.co/xwen-team/Xwen-7B-Chat 

Xwen 7B Chat Benchmarks

MMLU Pro: 36.56
GPQA: 1.45
MUSR: 6.8
BBH: 30.92
IFEval: 68.64 vs 88 (so35)-22%
MATH Lvl 5: 45.09
LLME Score: 0.2734
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Xwen 7B Chat (xwen-team/Xwen-7B-Chat)
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Xwen 7B Chat Parameters and Internals

LLM NameXwen 7B Chat
Repository 🤗https://huggingface.co/xwen-team/Xwen-7B-Chat 
Base Model(s)  Qwen/Qwen2.5-7B   Qwen/Qwen2.5-7B
Model Size7b
Required VRAM15.2 GB
Updated2026-04-05
Maintainerxwen-team
Model Typeqwen2
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
Supported Languagesen zh
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.46.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Xwen 7B Chat

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B Preview986K / 15.2 GB50
Qwen2.5 7B Instruct 1M986K / 15.4 GB101838363
Hush Qwen2.5 7B V1.2986K / 15.2 GB31
Hush Qwen2.5 7B V1.1986K / 15.2 GB61
Hush Qwen2.5 7B V1.4986K / 15.2 GB41
Hush Qwen2.5 7B Preview986K / 15.2 GB50
Hush Qwen2.5 7B V1.3986K / 15.2 GB42
Hush Qwen2.5 7B RP V1.4 1M986K / 15.2 GB42
Qwen 2.5 7B Exp Sce986K / 15.2 GB82
Qwen2.5 7B MixStock V0.1986K / 15.2 GB303
Note: green Score (e.g. "73.2") means that the model is better than xwen-team/Xwen-7B-Chat.

Rank the Xwen 7B Chat 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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