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RigoChat 7B V2 by IIC

 »  All LLMs  »  IIC  »  RigoChat 7B V2   URL Share it on

  210   
  Arxiv:1910.09700   Arxiv:2106.09685   Arxiv:2305.18290   Arxiv:2503.08188   Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins...   Chat   Conversational   Doi:10.57967/hf/4158   Endpoints compatible   Es   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/IIC/RigoChat-7b-v2 

RigoChat 7B V2 Benchmarks

LLME Score: 0.24485
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
RigoChat 7B V2 (IIC/RigoChat-7b-v2)

RigoChat 7B V2 Parameters and Internals

LLM NameRigoChat 7B V2
Repository 🤗https://huggingface.co/IIC/RigoChat-7b-v2 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2025-03-18
MaintainerIIC
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
Supported Languageses
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.45.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to RigoChat 7B V2

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Context / RAM
Downloads
Likes
Qwen2.5 7B Instruct 1M986K / 15.4 GB330617269
Hush Qwen2.5 7B RP V1.4 1M986K / 15.2 GB422
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Qwen2.5 7B CelestialHarmony 1M986K / 14.8 GB1477
Q2.5 Instruct 1M Harmony986K / 15.2 GB551
Impish QWEN 7B 1M986K / 15.2 GB784
COCO 7B Instruct 1M986K / 15.2 GB794
Apollo 7B986K / 15.2 GB490
Qwen2.5 7B Instruct 1M986K / 15.2 GB11172
Qwen2.5 7B Sky R1 Mini986K / 15.2 GB610
Note: green Score (e.g. "73.2") means that the model is better than IIC/RigoChat-7b-v2.

Rank the RigoChat 7B V2 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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