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Ct2fast Codegen 2B Mono by michaelfeil

 »  All LLMs  »  michaelfeil  »  Ct2fast Codegen 2B Mono   URL Share it on

  10   
  Arxiv:2203.13474   Codegen   Ctranslate2   Endpoints compatible   Float16   Int8   Region:us
Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-codegen-2B-mono 

Ct2fast Codegen 2B Mono Benchmarks

LLME Score: 0.10095
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ct2fast Codegen 2B Mono (michaelfeil/ct2fast-codegen-2B-mono)

Ct2fast Codegen 2B Mono Parameters and Internals

Model Type 
autoregressive, language model
Use Cases 
Areas:
program synthesis
Primary Use Cases:
Generating executable code given English prompts
Limitations:
Model is best at program synthesis
Considerations:
Prompts should be in form of comment string.
Additional Notes 
This is a quantized version of Salesforce/codegen-2B-mono to improve inference speed and reduce memory usage.
Training Details 
Data Sources:
BigPython dataset
Data Volume:
71.7B tokens
Methodology:
Cross-entropy loss to maximize likelihood of sequential inputs
Hardware Used:
Multiple TPU-v4-512
LLM NameCt2fast Codegen 2B Mono
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-codegen-2B-mono 
Model Size2b
Required VRAM5.6 GB
Updated2025-03-12
Maintainermichaelfeil
Model Files  5.6 GB
Generates CodeYes
Model ArchitectureAutoModel
Licensebsd-3-clause
Model Max Length2048
Tokenizer ClassCodeGenTokenizer

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Ct2fast Codegen 2B Multi0K / 5.6 GB131
Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-codegen-2B-mono.

Rank the Ct2fast Codegen 2B Mono Capabilities

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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 v20241227
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