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Ct2fast Codet5p 770M by michaelfeil

 »  All LLMs  »  michaelfeil  »  Ct2fast Codet5p 770M   URL Share it on

  5   
  Arxiv:2305.07922   Ctranslate2   Endpoints compatible   Float16   Int8   Region:us
Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-codet5p-770m 

Ct2fast Codet5p 770M Benchmarks

LLME Score: 0.09472
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ct2fast Codet5p 770M (michaelfeil/ct2fast-codet5p-770m)

Ct2fast Codet5p 770M Parameters and Internals

Model Type 
encoder-decoder, encoder-only, decoder-only
Use Cases 
Areas:
research, commercial applications
Applications:
code understanding, code generation
Primary Use Cases:
text-to-code generation, code completion, text-to-code retrieval, code retrieval-augmented generation
Additional Notes 
Performance gains observed in zero-shot, finetuning, and instruction-tuning settings.
Supported Languages 
c (high), c++ (high), c-sharp (high), go (high), java (high), javascript (high), php (high), python (high), ruby (high)
Training Details 
Data Sources:
github-code dataset
Data Volume:
stricter permissive subset
Methodology:
span denoising, causal language modeling, contrastive learning, text-code matching
Model Architecture:
shallow encoder and deep decoder
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Utilizes quantized inference methods via CTranslate2 for efficiency.
Release Notes 
Version:
converted
Date:
2023-05-20
Notes:
Quantized version using CTranslate2 for efficient inference.
LLM NameCt2fast Codet5p 770M
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-codet5p-770m 
Model Size770m
Required VRAM1.5 GB
Updated2025-05-20
Maintainermichaelfeil
Model Files  1.5 GB
Model ArchitectureAutoModel
Licensebsd-3-clause
Model Max Length512
Tokenizer ClassRobertaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-codet5p-770m.

Rank the Ct2fast Codet5p 770M 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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Release v20241227
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