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Ct2fast GPT Bigcode Santacoder by michaelfeil

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  Code   Ctranslate2   Dataset:bigcode/the-stack   Float16   Int8   Model-index   Region:us
Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-gpt_bigcode-santacoder 

Ct2fast GPT Bigcode Santacoder Benchmarks

LLME Score: 0.08667
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ct2fast GPT Bigcode Santacoder (michaelfeil/ct2fast-gpt_bigcode-santacoder)
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Ct2fast GPT Bigcode Santacoder Parameters and Internals

Model Type 
code generation, text generation
Use Cases 
Areas:
Research, Development
Applications:
Code generation, Software development
Primary Use Cases:
Generating code snippets, Filling in function bodies
Limitations:
Not suitable for instruction-based code generation, Can generate inaccurate or non-functional code
Considerations:
Use is intended for generating source code similar to input examples, and attribution may be required for verbatim code generation.
Additional Notes 
The quantized version allows faster inference with reduced memory, suitable for larger batch processing.
Supported Languages 
Java (high), JavaScript (high), Python (high)
Training Details 
Data Sources:
bigcode/the-stack
Data Volume:
236 billion tokens
Methodology:
Trained using GPT-2 architecture with multi-query attention and Fill-in-the-Middle objective
Training Time:
6.2 days
Hardware Used:
96 Tesla V100 GPUs
Model Architecture:
GPT-2 model with multi-query attention and Fill-in-the-Middle objective
Safety Evaluation 
Ethical Considerations:
The model may generate code that contains bugs or exploits. The code may also require attribution.
Responsible Ai Considerations 
Fairness:
The dataset was filtered for permissive licenses.
Accountability:
Users are responsible for ensuring proper attribution to any generated code that matches verbatim the dataset source code.
Input Output 
Input Format:
Source code templates or comments in Python, Java, or JavaScript
Accepted Modalities:
text
Output Format:
Code snippets or function body completion
Performance Tips:
The model performs better with context or template inputs similar to training data.
LLM NameCt2fast GPT Bigcode Santacoder
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-gpt_bigcode-santacoder 
Required VRAM2.2 GB
Updated2025-09-18
Maintainermichaelfeil
Model Files  2.2 GB
Supported Languagescode
Model ArchitectureAutoModel
Licenseopenrail
Model Max Length2048
Tokenizer ClassGPT2TokenizerFast
Errorsreplace

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

Rank the Ct2fast GPT Bigcode Santacoder 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 v20241124
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