GouMang by AI4Bread

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  Conversational   Custom code   Feature-extraction   Internlm2   Pytorch   Region:us   Sharded
Model Card on HF ๐Ÿค—: https://huggingface.co/AI4Bread/GouMang 

GouMang Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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GouMang Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research, commercial applications
Applications:
agricultural scenarios
Primary Use Cases:
tuber crop cultivation, pest and disease control, soil management
Limitations:
may produce biased or harmful content
Considerations:
Care should be taken to not propagate biased or harmful content.
Additional Notes 
Model will be continuously optimized based on user feedback and latest research findings.
Supported Languages 
Chinese (high proficiency), English (high proficiency)
Safety Evaluation 
Risk Categories:
bias, discrimination
Ethical Considerations:
The model may produce outputs that contain biases, discrimination, or harmful content. Users should not propagate such content.
Input Output 
Performance Tips:
Employs advanced training algorithms for quick and efficient Q&A services.
LLM NameGouMang
Repository ๐Ÿค—https://huggingface.co/AI4Bread/GouMang 
Model Size7b
Required VRAM15.4 GB
Updated2024-12-04
MaintainerAI4Bread
Model Typeinternlm2
Model Files  1.9 GB: 1-of-8   1.9 GB: 2-of-8   2.0 GB: 3-of-8   1.9 GB: 4-of-8   2.0 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   1.8 GB: 8-of-8
Model ArchitectureInternLM2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Is Biased0
Tokenizer ClassInternLM2Tokenizer
Padding Token</s>
Vocabulary Size92544
Torch Data Typefloat16
GouMang (AI4Bread/GouMang)

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Note: green Score (e.g. "73.2") means that the model is better than AI4Bread/GouMang.

Rank the GouMang 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