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OpenR1 Qwen 7B by open-r1

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OpenR1 Qwen 7B is an open-source language model by open-r1. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.19.

  Conversational Dataset:open-r1/openr1-220k-ma...   Endpoints compatible   Generated from trainer   Instruct   Qwen2   Region:us   Safetensors   Sft   Sharded   Tensorflow   Trl
Model Card on HF 🤗: https://huggingface.co/open-r1/OpenR1-Qwen-7B 

OpenR1 Qwen 7B Benchmarks

LLME Score: 0.18704
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OpenR1 Qwen 7B (open-r1/OpenR1-Qwen-7B)
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OpenR1 Qwen 7B Parameters and Internals

LLM NameOpenR1 Qwen 7B
Repository 🤗https://huggingface.co/open-r1/OpenR1-Qwen-7B 
Model NameOpenR1-Qwen-7B
Model Size7b
Required VRAM15.2 GB
Updated2026-04-07
Maintaineropen-r1
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   0.0 GB
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.49.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|im_end|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to OpenR1 Qwen 7B

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B Instruct 1M986K / 15.4 GB101838363
Hush Qwen2.5 7B RP V1.4 1M986K / 15.2 GB42
Qwen2.5 7B RRP 1M986K / 15.2 GB46
Qwen2.5 7B CelestialHarmony 1M986K / 14.8 GB37
Q2.5 Instruct 1M Harmony986K / 15.2 GB42
Impish QWEN 7B 1M986K / 15.2 GB76
COCO 7B Instruct 1M986K / 15.2 GB184
Apollo 7B986K / 15.2 GB60
Graph R1 7B986K / 15.3 GB53
Qwen2.5 7B Sky R1 Mini986K / 15.2 GB70
Note: green Score (e.g. "73.2") means that the model is better than open-r1/OpenR1-Qwen-7B.

Rank the OpenR1 Qwen 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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