Qwen2.5 Microsoft NextCoder Brainstorm20x 42B by DavidAU

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  Arxiv:2401.02415   Autotrain compatible Base model:finetune:microsoft/... Base model:microsoft/nextcoder...   Brainstorm   Brainstorm20x   Chat   Code   Code generation   Codegen   Codeqwen   Coder   Coding   Conversational   Dataset:bigcode/commitpackft   Dataset:bigcode/starcoderdata Dataset:microsoft/nextcoderdat... Dataset:microsoft/nextcoderdat...   En   Endpoints compatible   Merge   Microsoft   Nextcoder   Qwen   Qwen-coder   Qwen2   Region:us   Safetensors   Selekt   Sharded   Tensorflow

Qwen2.5 Microsoft NextCoder Brainstorm20x 42B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 Microsoft NextCoder Brainstorm20x 42B (DavidAU/Qwen2.5-Microsoft-NextCoder-Brainstorm20x-42B)
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Qwen2.5 Microsoft NextCoder Brainstorm20x 42B Parameters and Internals

LLM NameQwen2.5 Microsoft NextCoder Brainstorm20x 42B
Repository ๐Ÿค—https://huggingface.co/DavidAU/Qwen2.5-Microsoft-NextCoder-Brainstorm20x-42B 
Base Model(s)  NextCoder 32B   microsoft/NextCoder-32B
Model Size32b
Required VRAM84.3 GB
Updated2025-07-19
MaintainerDavidAU
Model Typeqwen2
Model Files  5.0 GB: 1-of-18   5.0 GB: 2-of-18   4.9 GB: 3-of-18   4.9 GB: 4-of-18   4.9 GB: 5-of-18   4.9 GB: 6-of-18   4.9 GB: 7-of-18   4.9 GB: 8-of-18   4.9 GB: 9-of-18   4.9 GB: 10-of-18   4.9 GB: 11-of-18   4.9 GB: 12-of-18   4.9 GB: 13-of-18   4.8 GB: 14-of-18   4.8 GB: 15-of-18   4.8 GB: 16-of-18   5.0 GB: 17-of-18   1.0 GB: 18-of-18
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.52.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than DavidAU/Qwen2.5-Microsoft-NextCoder-Brainstorm20x-42B.

Rank the Qwen2.5 Microsoft NextCoder Brainstorm20x 42B Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124