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Ct2fast Codegen 2B Multi by michaelfeil

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

  7   
  Arxiv:2203.13474   Codegen   Ctranslate2   Endpoints compatible   Float16   Int8   Region:us
Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-codegen-2B-multi 

Ct2fast Codegen 2B Multi Benchmarks

LLME Score: 0.10882
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 Multi (michaelfeil/ct2fast-codegen-2B-multi)

Ct2fast Codegen 2B Multi Parameters and Internals

Model Type 
autoregressive, language model
Use Cases 
Areas:
Research, Code generation
Applications:
Program synthesis
Primary Use Cases:
Generating executable code from English prompts
Limitations:
The model is primarily intended for program synthesis., It may not be suitable for tasks outside code generation.
Considerations:
Prompts should preferably be in the form of a comment string.
Additional Notes 
Benchmarks used for evaluation include HumanEval and MTPB.
Supported Languages 
English (proficient), C (supported), C++ (supported), Go (supported), Java (supported), JavaScript (supported), Python (supported)
Training Details 
Data Sources:
BigQuery, GitHub repositories
Data Volume:
119.2B tokens
Methodology:
Pre-trained on multiple programming languages
Hardware Used:
TPU-v4-512
Model Architecture:
Transformer-based
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Generated code
Performance Tips:
Use int8_float16 for CUDA device to optimize performance.
Release Notes 
Version:
Initial Version
Date:
2023-05-21
Notes:
Quantized version of CodeGen-Multi 6B.
LLM NameCt2fast Codegen 2B Multi
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-codegen-2B-multi 
Model Size2b
Required VRAM5.6 GB
Updated2024-12-22
Maintainermichaelfeil
Model Files  5.6 GB
Generates CodeYes
Model ArchitectureAutoModel
Licensebsd-3-clause
Model Max Length2048
Tokenizer ClassCodeGenTokenizer

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Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-codegen-2B-multi.

Rank the Ct2fast Codegen 2B Multi 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 v20241217
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