MuseNeo by breadlicker45

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  Autotrain compatible Dataset:breadlicker45/midi-mus...   Endpoints compatible   Gpt neo   Pytorch   Region:us   Safetensors
Model Card on HF ๐Ÿค—: https://huggingface.co/breadlicker45/MuseNeo 

MuseNeo Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MuseNeo (breadlicker45/MuseNeo)
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MuseNeo Parameters and Internals

Model Type 
music generation
Use Cases 
Primary Use Cases:
music composition
Additional Notes 
The model will not be trained further. Successor: MusePy.
Training Details 
Data Sources:
breadlicker45/midi-music-codes
Data Volume:
393 midi songs
Training Time:
84k steps
LLM NameMuseNeo
Repository ๐Ÿค—https://huggingface.co/breadlicker45/MuseNeo 
Model Size175.5m
Required VRAM0.6 GB
Updated2025-09-23
Maintainerbreadlicker45
Model Typegpt_neo
Model Files  0.6 GB   0.6 GB
Model ArchitectureGPTNeoForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Transformers Version4.20.1
Vocabulary Size50257
Torch Data Typefloat32
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than breadlicker45/MuseNeo.

Rank the MuseNeo 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