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PolyCoder 160M by NinedayWang

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PolyCoder 160M is an open-source language model by NinedayWang. Features: 160m LLM, VRAM: 0.7GB, Context: 2K, LLM Explorer Score: 0.05.

  Arxiv:2202.13169   Deploy:azure   Endpoints compatible   Gpt neox   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/NinedayWang/PolyCoder-160M 

PolyCoder 160M Benchmarks

LLME Score: 0.04771
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
PolyCoder 160M (NinedayWang/PolyCoder-160M)
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PolyCoder 160M Parameters and Internals

Model Type 
text generation, code generation
Additional Notes 
Trained across 12 programming languages.
Training Details 
Data Sources:
code
Data Volume:
249 GB
LLM NamePolyCoder 160M
Repository 🤗https://huggingface.co/NinedayWang/PolyCoder-160M 
Model Size160m
Required VRAM0.7 GB
Updated2026-05-26
MaintainerNinedayWang
Model Typegpt_neox
Model Files  0.7 GB   0.7 GB
Model ArchitectureGPTNeoXForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.23.1
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size50304
Torch Data Typefloat32
Errorsreplace

Best Alternatives to PolyCoder 160M

Best Alternatives
Context / RAM
Downloads
Likes
Pythia 160M C2s8K / 0.6 GB11476
Pythia 160M2K / 0.4 GB309562742
Pythia 160M Xsum Roya2K / 0.6 GB210
Pythia 160M Deduped2K / 0.4 GB888663
Pythia 160m Sft2K / 0 GB70
Sheared Pythia 160M2K / 0.7 GB8704
Pythia 160M Dolphin Extended2K / 0.3 GB7200
...hia 160M Deduped Step92k 193bt2K / 0.4 GB9730
Pythia 160M Storytelling2K / 0.3 GB90
Pythia160m Sft Tldr2K / 0.6 GB100
Note: green Score (e.g. "73.2") means that the model is better than NinedayWang/PolyCoder-160M.

Rank the PolyCoder 160M 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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