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Diff Codegen 6B V2 by CarperAI

 »  All LLMs  »  CarperAI  »  Diff Codegen 6B V2   URL Share it on

  140   
  Arxiv:2101.00027   Arxiv:2201.07311   Arxiv:2203.13474   Autotrain compatible   Code   Code-generation   Codegen   Diff model   En   Endpoints compatible   Pytorch   Region:us   Safetensors   The pile
Model Card on HF 🤗: https://huggingface.co/CarperAI/diff-codegen-6b-v2 

Diff Codegen 6B V2 Benchmarks

LLME Score: 0.07817
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Diff Codegen 6B V2 (CarperAI/diff-codegen-6b-v2)

Diff Codegen 6B V2 Parameters and Internals

Model Type 
causal-lm, code-generation
Use Cases 
Primary Use Cases:
Prototyping code generation systems, Experimental purposes
Limitations:
Underperform on underrepresented languages, Not suitable for mission-critical settings
Additional Notes 
Suggested for use in experiments, not commercial settings. Caution advised due to potential security vulnerabilities.
Training Details 
Data Sources:
The Pile, GitHub commits via Google BigQuery Public Dataset
Data Volume:
19 million commits
Methodology:
Fine-tuned on a large dataset of commits. Formatted using Unified Diff Format for input to the language model.
Context Length:
2048
Hardware Used:
64 A100 GPUs provided by Stability AI
Input Output 
Input Format:
Formatted as Unified Diff Format.
Accepted Modalities:
code
Output Format:
Code in diff format.
LLM NameDiff Codegen 6B V2
Repository 🤗https://huggingface.co/CarperAI/diff-codegen-6b-v2 
Model Size6b
Required VRAM14.3 GB
Updated2025-03-12
MaintainerCarperAI
Model Typecodegen
Model Files  14.3 GB   14.3 GB
Supported Languagesen code
Generates CodeYes
Model ArchitectureCodeGenForCausalLM
Licensemit
Model Max Length2048
Transformers Version4.22.0.dev0
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50295
Torch Data Typefloat16
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than CarperAI/diff-codegen-6b-v2.

Rank the Diff Codegen 6B V2 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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Release v20241227
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