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CodeLlama 7B Instruct Hf by codellama

 »  All LLMs  »  codellama  »  CodeLlama 7B Instruct Hf   URL Share it on

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  Arxiv:2308.12950   Autotrain compatible   Code   Codegen   Conversational   Endpoints compatible   Instruct   Llama   Llama2   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf 

CodeLlama 7B Instruct Hf Benchmarks

ARC: 36.52 vs 96.7 (so35)-62.2%
HellaSwag: 55.44 vs 95.3 (gpt4)-41.8%
MMLU: 34.54 vs 88.3 (so35)-60.9%
TruthfulQA: 41.25 vs 59 (gpt4)-30.1%
WinoGrande: 64.56 vs 87.5 (gpt4)-26.2%
GSM8K: 7.96 vs 96.4 (so35)-91.7%
HumanEvalA: 26.45
Python Eva: 45.65 vs 92 (so35)-50.4%
Java Eval: 28.77
Javascript: 33.11
CPP Eval: 29.03
PHP Eval: 28.55
Julia Eval: 27.58
D Eval: 11.81
Lua Eval: 30.47
R Eval: 19.7
Racket Eva: 11.81
Rust Eval: 24.27
Swift Eval: 26.66
LLME Score: 0.26932
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CodeLlama 7B Instruct Hf (codellama/CodeLlama-7b-Instruct-hf)

CodeLlama 7B Instruct Hf Parameters and Internals

Model Type 
generative, text-generation
Use Cases 
Areas:
Commercial, Research
Applications:
Code synthesis, Code understanding, Code assistant and generation applications
Primary Use Cases:
General code synthesis, Python programming, Instruction following
Limitations:
Output in languages other than English is not recommended., Use in any manner that violates applicable laws or regulations is prohibited.
Considerations:
Developers should perform safety testing and tuning tailored to their specific applications.
Additional Notes 
This is a static model trained on an offline dataset.
Supported Languages 
primary_language (English), specialties (Programming languages, primarily Python)
Training Details 
Data Sources:
Same data as Llama 2
Methodology:
Trained with custom libraries on Meta’s Research Super Cluster
Hardware Used:
A100-80GB GPUs
Model Architecture:
Auto-regressive language model using an optimized transformer architecture
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text
LLM NameCodeLlama 7B Instruct Hf
Repository 🤗https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf 
Model Size7b
Required VRAM13.5 GB
Updated2025-01-19
Maintainercodellama
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2   4.9 GB: 1-of-3   5.0 GB: 2-of-3   3.6 GB: 3-of-3
Supported Languagescode
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length16384
Model Max Length16384
Transformers Version4.33.0.dev0
Tokenizer ClassCodeLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32016
Torch Data Typebfloat16

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Rank the CodeLlama 7B Instruct Hf 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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