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CodeLlama 13B Hf by codellama

 »  All LLMs  »  codellama  »  CodeLlama 13B Hf   URL Share it on

  8498   
  Arxiv:2308.12950   Autotrain compatible   Code   Codegen   Endpoints compatible   Llama   Llama2   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/codellama/CodeLlama-13b-hf 

CodeLlama 13B Hf Benchmarks

ARC: 40.87 vs 96.7 (so35)-57.7%
HellaSwag: 63.35 vs 95.3 (gpt4)-33.5%
MMLU: 32.81 vs 88.3 (so35)-62.8%
TruthfulQA: 43.79 vs 59 (gpt4)-25.8%
WinoGrande: 67.17 vs 87.5 (gpt4)-23.2%
GSM8K: 12.13 vs 96.4 (so35)-87.4%
HumanEvalA: 28.35
Python Eva: 35.07 vs 92 (so35)-61.9%
Java Eval: 32.23
Javascript: 38.26
CPP Eval: 35.81
PHP Eval: 32.57
Julia Eval: 28.01
D Eval: 15.78
Lua Eval: 31.26
R Eval: 18.32
Racket Eva: 13.63
Rust Eval: 29.72
Swift Eval: 29.54
LLME Score: 0.19437
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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CodeLlama 13B Hf Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
commercial, research
Applications:
code synthesis, understanding tasks, handling Python programming
Primary Use Cases:
code assistant and generation applications
Limitations:
Use in languages other than English, Using violating laws or regulations
Considerations:
Follow Acceptable Use Policy and Licensing Agreement
Additional Notes 
This is a non-official Code Llama repo. Official repository available at Meta's Llama organization on Hugging Face.
Supported Languages 
English (high proficiency)
Training Details 
Data Sources:
same data as Llama 2
Data Volume:
Not specified
Methodology:
Pre-trained and fine-tuned generative text models
Training Time:
January 2023 to July 2023
Hardware Used:
Meta’s Research Super Cluster with A100-80GB GPUs
Model Architecture:
auto-regressive language model using an optimized transformer architecture
Safety Evaluation 
Methodologies:
community feedback
Risk Categories:
misinformation, bias
Ethical Considerations:
Potential to produce inaccurate or objectionable responses
Responsible Ai Considerations 
Fairness:
Testing conducted only in English; may not cover all scenarios
Transparency:
Outputs cannot be predicted in advance
Accountability:
Developers should perform safety testing and application tuning
Mitigation Strategies:
Responsible Use Guide available at Meta's website
Input Output 
Input Format:
text only
Accepted Modalities:
text
Output Format:
text only
LLM NameCodeLlama 13B Hf
Repository 🤗https://huggingface.co/codellama/CodeLlama-13b-hf 
Model Size13b
Required VRAM26 GB
Updated2025-06-09
Maintainercodellama
Model Typellama
Model Files  9.9 GB: 1-of-3   9.9 GB: 2-of-3   6.2 GB: 3-of-3   9.9 GB: 1-of-3   9.9 GB: 2-of-3   6.5 GB: 3-of-3
Supported Languagescode
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length16384
Model Max Length16384
Transformers Version4.32.0.dev0
Tokenizer ClassCodeLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32016
Torch Data Typebfloat16
CodeLlama 13B Hf (codellama/CodeLlama-13b-hf)

Quantized Models of the CodeLlama 13B Hf

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Likes
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VRAM
CodeLlama 13B GGUF6136915 GB
CodeLlama 13B AWQ4197 GB
CodeLlama 13B GPTQ11967 GB
CodeLlama 13B GGML33155 GB

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Note: green Score (e.g. "73.2") means that the model is better than codellama/CodeLlama-13b-hf.

Rank the CodeLlama 13B 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 v20241124
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