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Gogpt 560M by golaxy

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Gogpt 560M is an open-source language model by golaxy. Features: 560m LLM, VRAM: 1GB, License: apache-2.0, LLM Explorer Score: 0.13, Arc: 26.4, HellaSwag: 31.9, MMLU: 25.3.

  Bloom Dataset:bellegroup/school math... Dataset:bellegroup/train 0.5m ...   Dataset:bellegroup/train 1m cn   Dataset:bellegroup/train 2m cn Dataset:bellegroup/train 3.5m ...   Endpoints compatible   Pytorch   Region:us   Zh
Model Card on HF 🤗: https://huggingface.co/golaxy/gogpt-560m 

Gogpt 560M Benchmarks

ARC: 26.37 vs 96.7 (so35)-72.7%
HellaSwag: 31.86 vs 95.3 (gpt4)-66.6%
MMLU: 25.29 vs 88.3 (so35)-71.4%
LLME Score: 0.1292
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gogpt 560M (golaxy/gogpt-560m)
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Gogpt 560M Parameters and Internals

Model Type 
Instruction-tuned
Use Cases 
Areas:
Research, Commercial applications
Limitations:
Limited by the quality of input datasets, Focus on Chinese instructions
Additional Notes 
Model is tailored for Chinese instructions using diverse and high-quality datasets.
Supported Languages 
zh (fluent)
Training Details 
Data Sources:
BelleGroup/train_2M_CN, BelleGroup/train_3.5M_CN, BelleGroup/train_1M_CN, BelleGroup/train_0.5M_CN, BelleGroup/school_math_0.25M
Methodology:
Instruction tuning on BLOOM using Chinese datasets
LLM NameGogpt 560M
Repository 🤗https://huggingface.co/golaxy/gogpt-560m 
Model Size560m
Required VRAM1 GB
Updated2026-05-17
Maintainergolaxy
Model Typebloom
Model Files  1.0 GB   2.2 GB   0.0 GB
Supported Languageszh
Model ArchitectureBloomForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.29.1
Tokenizer ClassBloomTokenizer
Padding Token<pad>
Vocabulary Size250880
Torch Data Typefloat32

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Product Description Fr0K / 2.2 GB50
Note: green Score (e.g. "73.2") means that the model is better than golaxy/gogpt-560m.

Rank the Gogpt 560M 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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