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Diff Codegen 2B V2 by CarperAI

 »  All LLMs  »  CarperAI  »  Diff Codegen 2B V2   URL Share it on

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  Arxiv:2101.00027   Arxiv:2201.07311   Arxiv:2203.13474   Autotrain compatible   Code   Code-generation   Codegen   Diff model   En   Endpoints compatible   Pytorch   Region:us   The pile
Model Card on HF 🤗: https://huggingface.co/CarperAI/diff-codegen-2b-v2 

Diff Codegen 2B V2 Benchmarks

LLME Score: 0.0763
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Diff Codegen 2B V2 (CarperAI/diff-codegen-2b-v2)

Diff Codegen 2B 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 2B V2
Repository 🤗https://huggingface.co/CarperAI/diff-codegen-2b-v2 
Model Size2b
Required VRAM5.7 GB
Updated2025-02-22
MaintainerCarperAI
Model Typecodegen
Model Files  5.7 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-2b-v2.

Rank the Diff Codegen 2B V2 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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