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Shlonak Qwen25 Shami V6 by mtarros

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Shlonak Qwen25 Shami V6 is an open-source language model by mtarros. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.27.

  4bit   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors   Unsloth
Model Card on HF 🤗: https://huggingface.co/mtarros/shlonak-qwen25-shami-v6 

Shlonak Qwen25 Shami V6 Benchmarks

LLME Score: 0.2671
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Shlonak Qwen25 Shami V6 (mtarros/shlonak-qwen25-shami-v6)
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Shlonak Qwen25 Shami V6 Parameters and Internals

LLM NameShlonak Qwen25 Shami V6
Repository 🤗https://huggingface.co/mtarros/shlonak-qwen25-shami-v6 
Base Model(s)  unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit   unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit
Model Size1.5b
Required VRAM3.1 GB
Updated2026-05-10
Maintainermtarros
Model Typeqwen2
Instruction-BasedYes
Model Files  3.1 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than mtarros/shlonak-qwen25-shami-v6.

Rank the Shlonak Qwen25 Shami V6 Capabilities

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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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