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Zariman R 7B V0 by attn-signs

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Zariman R 7B V0 is an open-source language model by attn-signs. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.18.

Base model:attn-signs/watari-7... Base model:finetune:attn-signs...   Conversational Dataset:attn-signs/russian-rea...   Endpoints compatible   Qwen2   Region:us   Ru   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/attn-signs/Zariman-R-7b-v0 

Zariman R 7B V0 Benchmarks

LLME Score: 0.18082
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Zariman R 7B V0 (attn-signs/Zariman-R-7b-v0)
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Zariman R 7B V0 Parameters and Internals

LLM NameZariman R 7B V0
Repository 🤗https://huggingface.co/attn-signs/Zariman-R-7b-v0 
Base Model(s)  attn-signs/Watari-7b-v1   attn-signs/Watari-7b-v1
Model Size7b
Required VRAM15.2 GB
Updated2026-03-30
Maintainerattn-signs
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 Languagesru
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.48.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151666
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Zariman R 7B V0

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 Preview986K / 15.2 GB400
Hush Qwen2.5 7B V1.4986K / 15.2 GB41
Hush Qwen2.5 7B V1.3986K / 15.2 GB42
Hush Qwen2.5 7B RP V1.4 1M986K / 15.2 GB192
Qwen 2.5 7B Exp Sce986K / 15.2 GB82
Qwen2.5 7B MixStock V0.1986K / 15.2 GB333
Note: green Score (e.g. "73.2") means that the model is better than attn-signs/Zariman-R-7b-v0.

Rank the Zariman R 7B V0 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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