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QWQ Stock by wanlige

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QWQ Stock is an open-source language model by wanlige. Features: 32b LLM, VRAM: 65.8GB, Context: 32K, Instruction-Based, Merged, LLM Explorer Score: 0.19.

  Merged Model   Arxiv:2403.19522   Ara Base model:huihui-ai/deepseek-... Base model:maldv/awqward2.5-32...   Base model:qwen/qwen2.5-32b Base model:qwen/qwen2.5-32b-in...   Base model:qwen/qwq-32b Base model:qwen/qwq-32b-previe... Base model:tanliboy/lambda-qwe...   Conversational   Deu   Endpoints compatible   Eng   Fra   Instruct   Ita   Jpn   Kor   Por   Qwen2   Region:us   Rus   Safetensors   Sharded   Spa   Tensorflow   Tha   Vie   Zho
Model Card on HF 🤗: https://huggingface.co/wanlige/QWQ-stock 

QWQ Stock Benchmarks

LLME Score: 0.18542
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
QWQ Stock (wanlige/QWQ-stock)
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QWQ Stock Parameters and Internals

LLM NameQWQ Stock
Repository 🤗https://huggingface.co/wanlige/QWQ-stock 
Base Model(s)  Qwen/Qwen2.5-32B   QwQ 32B   maldv/Awqward2.5-32B-Instruct   ...1 Distill Qwen 32B Abliterated   QwQ 32B Preview   Qwen/Qwen2.5-32B-Instruct   tanliboy/lambda-qwen2.5-32b-dpo-test   Qwen/Qwen2.5-32B   Qwen/QwQ-32B   maldv/Awqward2.5-32B-Instruct   huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated   Qwen/QwQ-32B-Preview   Qwen/Qwen2.5-32B-Instruct   tanliboy/lambda-qwen2.5-32b-dpo-test
Merged ModelYes
Model Size32b
Required VRAM65.8 GB
Updated2026-04-04
Maintainerwanlige
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-14   5.0 GB: 2-of-14   4.9 GB: 3-of-14   4.9 GB: 4-of-14   4.9 GB: 5-of-14   4.9 GB: 6-of-14   4.9 GB: 7-of-14   4.9 GB: 8-of-14   4.9 GB: 9-of-14   4.9 GB: 10-of-14   4.9 GB: 11-of-14   4.9 GB: 12-of-14   4.9 GB: 13-of-14   1.9 GB: 14-of-14
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.48.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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...y Qwen2.5coder 32B V24.1q 200K195K / 65.8 GB122
...wen2.5 32B Inst BaseMerge TIES128K / 65.8 GB3117
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Franqwenstein 35B128K / 69.8 GB38
ELYZA Thinking 1.0 Qwen 32B128K / 65.8 GB12847
Hamanasu Magnum QwQ 32B128K / 65.8 GB2959
Archaeo 32B KTO128K / 65.8 GB44
Qwen2.5 32B Gokgok Step3128K / 65.7 GB60
Qwen2.5 32B Dark Days Stage2128K / 65.8 GB70
Qwen2.5 32B YOYO MIX128K / 65.7 GB52
Note: green Score (e.g. "73.2") means that the model is better than wanlige/QWQ-stock.

Rank the QWQ Stock 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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