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Qwen3 Wiki Sciq Mmlu by timarni

 »  All LLMs  »  timarni  »  Qwen3 Wiki Sciq Mmlu   URL Share it on

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Qwen3 Wiki Sciq Mmlu is an open-source language model by timarni. Features: 596m LLM, VRAM: 1.2GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.19.

Base model:finetune:timarni/qw... Base model:timarni/qwen3 pretr...   Conversational Dataset:timarni/mnlp dataset m...   Dataset:timarni/sciq alpaca   Endpoints compatible   Generated from trainer   Qwen3   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/timarni/qwen3_wiki_sciq_mmlu 

Qwen3 Wiki Sciq Mmlu Benchmarks

LLME Score: 0.19317
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen3 Wiki Sciq Mmlu (timarni/qwen3_wiki_sciq_mmlu)
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Qwen3 Wiki Sciq Mmlu Parameters and Internals

LLM NameQwen3 Wiki Sciq Mmlu
Repository 🤗https://huggingface.co/timarni/qwen3_wiki_sciq_mmlu 
Base Model(s)  Qwen3 Pretrain Wiki   timarni/qwen3_pretrain_wiki
Model Size596m
Required VRAM1.2 GB
Updated2026-05-15
Maintainertimarni
Model Typeqwen3
Model Files  1.2 GB
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.51.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Qwen3 Wiki Sciq Mmlu

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MNLP M3 DPO Sft200k CME32K / 2.4 GB200
Rubi No Reason Phase 232K / 1.2 GB60
... Reason Phase Only Ultrafeed 132K / 1.2 GB90
Note: green Score (e.g. "73.2") means that the model is better than timarni/qwen3_wiki_sciq_mmlu.

Rank the Qwen3 Wiki Sciq Mmlu 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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