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Qwen3 8B Rl490 With Think Knowledge Merged by didula-wso2

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Qwen3 8B Rl490 With Think Knowledge Merged is an open-source language model by didula-wso2. Features: 8b LLM, VRAM: 16.4GB, Context: 40K, License: apache-2.0, Quantized, LLM Explorer Score: 0.3.

  16bit Base model:didula-wso2/qwen3-8... Base model:finetune:didula-wso...   Conversational   En   Endpoints compatible   Quantized   Qwen3   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/didula-wso2/Qwen3-8B-rl490_with_think_knowledge_merged 

Qwen3 8B Rl490 With Think Knowledge Merged Benchmarks

LLME Score: 0.30059
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen3 8B Rl490 With Think Knowledge Merged (didula-wso2/Qwen3-8B-rl490_with_think_knowledge_merged)
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Qwen3 8B Rl490 With Think Knowledge Merged Parameters and Internals

LLM NameQwen3 8B Rl490 With Think Knowledge Merged
Repository 🤗https://huggingface.co/didula-wso2/Qwen3-8B-rl490_with_think_knowledge_merged 
Base Model(s)  ...ended With Thinksft 16bit Vllm   didula-wso2/Qwen3-8B-ep4_julia_codeforces_extended_with_thinksft_16bit_vllm
Model Size8b
Required VRAM16.4 GB
Updated2026-06-01
Maintainerdidula-wso2
Model Typeqwen3
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   1.6 GB: 4-of-4
Supported Languagesen
Quantization Type16bit
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length40960
Model Max Length40960
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 didula-wso2/Qwen3-8B-rl490_with_think_knowledge_merged.

Rank the Qwen3 8B Rl490 With Think Knowledge Merged 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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