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what is codellama fr?

meta-llama/codellama — explained in plain English

Analysis updated 2026-06-24

16,327PythonAudience · developerComplexity · 4/5Setup · hard

tl;dr

The official Python inference code for Meta's Code Llama AI models, specialized for understanding and writing code, available in sizes from 7B to 70B parameters for self-hosting on your own GPU hardware.

vibe map

mindmap
  root((Code Llama))
    Model Variants
      Base completion
      Python specialized
      Instruct chat style
    Model Sizes
      7B and 13B
      34B and 70B
    Key Features
      Code infilling
      100K token context
      Local self-hosting
    Requirements
      CUDA GPU
      PyTorch
      Meta download access

Code map

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filefunction / class

what do people make with this?

VIBE 1

Run a local AI code completion model that fills in gaps in existing code without sending data to a third-party API

VIBE 2

Self-host a 7B coding model for fast autocomplete in a private development environment

VIBE 3

Use Code Llama Instruct in a conversational style to ask coding questions and get detailed answers

VIBE 4

Build a custom code review or generation pipeline using the 34B or 70B model for higher accuracy

what's the stack?

PythonPyTorchCUDA

how it stacks up fr

meta-llama/codellamanvidia/megatron-lmqwenlm/qwen-agent
Stars16,32716,32216,321
LanguagePythonPythonPython
Setup difficultyhardhardmoderate
Complexity4/55/53/5
Audiencedeveloperresearcherdeveloper

Figures from each repo's GitHub metadata at analysis time.

how do i run it?

Difficulty · hard time til it works · 1day+

Requires CUDA GPU with at least 12.5 GB VRAM for the smallest model and Meta download approval before you can start.

in plain english

Code Llama is a family of large language models (AI systems trained on vast amounts of text and code) released by Meta, specialized for understanding and generating code. This repository contains the Python inference code, the scripts needed to load Code Llama model weights and run them locally to get predictions. The family comes in multiple flavors: base models (Code Llama) for code completion, Python-specialized models (Code Llama - Python) tuned further on Python code, and instruction-following models (Code Llama - Instruct) that you can prompt in conversational style to ask coding questions. Each flavor is available in sizes of 7 billion, 13 billion, 34 billion, and 70 billion parameters, larger models are generally more capable but require more memory and hardware. The 7B model requires about 12.55 GB of storage, while the 70B model requires about 131 GB. A notable feature is code infilling: the 7B and 13B base and instruct models can fill in a gap in existing code based on the surrounding context, useful for autocomplete-style features. All models support input contexts of up to 100,000 tokens, meaning they can consider large amounts of existing code when generating. To use the models, you request download access via Meta's website, download the weights, and run inference locally using PyTorch with CUDA (a GPU computing framework). This is for developers who want to run Code Llama on their own infrastructure rather than calling a hosted API. The full README is longer than what was provided.

prompts (copy fr)

prompt 1
How do I download and run Meta's Code Llama 7B model locally to autocomplete Python functions using this repository?
prompt 2
Write a Python script using the Code Llama inference code to fill in a gap marked with a placeholder in an existing function
prompt 3
What GPU memory do I need to run the Code Llama 34B model from this repository, and how do I start it?
prompt 4
How do I use Code Llama Instruct to ask it to refactor a piece of code in a conversational back-and-forth style?
prompt 5
Walk me through requesting download access from Meta and setting up the model weights for the 13B Code Llama model

Frequently asked questions

what is codellama fr?

The official Python inference code for Meta's Code Llama AI models, specialized for understanding and writing code, available in sizes from 7B to 70B parameters for self-hosting on your own GPU hardware.

What language is codellama written in?

Mainly Python. The stack also includes Python, PyTorch, CUDA.

How hard is codellama to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is codellama for?

Mainly developer.

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This repo across BitVibe Labs

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