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Qwen2.5 7B by unsloth

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Qwen2.5 7B is an open-source language model by unsloth. Features: 7b LLM, VRAM: 15.2GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.24.

  Arxiv:2407.10671   Ara Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-7b   Deu   Endpoints compatible   Eng   Fra   Ita   Jpn   Kor   Por   Qwen2   Region:us   Rus   Safetensors   Sharded   Spa   Tensorflow   Tha   Unsloth   Vie   Zho
Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen2.5-7B 

Qwen2.5 7B Benchmarks

LLME Score: 0.2392
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 7B (unsloth/Qwen2.5-7B)
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Qwen2.5 7B Parameters and Internals

Model Type 
Causal Language Model
Use Cases 
Areas:
Research, Coding, Mathematics, Multilingual Applications
Applications:
Chatbots, Structured Data Understanding, Role-playing Implementations
Primary Use Cases:
instruction following, generating long texts, understanding structured data, generating structured outputs
Limitations:
Not recommended for conversations without further training
Considerations:
Use post-training methods for conversations like SFT, RLHF
Additional Notes 
Supports multilingual capabilities with improved role-play conditions for chatbots.
Supported Languages 
English (high), Chinese (high), French (medium), Spanish (medium), Portuguese (medium), German (medium), Italian (medium), Russian (medium), Japanese (medium), Korean (medium), Vietnamese (medium), Thai (medium), Arabic (medium), other_languages (basic)
Training Details 
Data Sources:
specialized expert models in coding and mathematics
Context Length:
131072
Model Architecture:
transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use the latest version of 'transformers' to avoid errors.
LLM NameQwen2.5 7B
Repository 🤗https://huggingface.co/unsloth/Qwen2.5-7B 
Base Model(s)  Qwen/Qwen2.5-7B   Qwen/Qwen2.5-7B
Model Size7b
Required VRAM15.2 GB
Updated2026-03-30
Maintainerunsloth
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
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.49.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the Qwen2.5 7B

Model
Likes
Downloads
VRAM
Krx Q25 7B Base V3013315 GB
Krx Q25 7B Base V208815 GB
Krx Q25 7B Base07415 GB
Sejong Qwen V11015 GB

Best Alternatives to Qwen2.5 7B

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B Preview986K / 15.2 GB50
Qwen2.5 7B Instruct 1M986K / 15.4 GB101142362
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 GB42
Qwen2.5 7B MixStock V0.1986K / 15.2 GB73
Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen2.5-7B.

Rank the Qwen2.5 7B 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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