Activefrontierllm Open Source

Code Llama 70B

by Meta· Released January 2024· Cutoff January 2023

Code Llama 70B is Meta's largest code-focused language model, designed for code generation, understanding, and debugging. It is built on Llama 2 and fine-tuned on code-heavy datasets, offering state-of-the-art performance among open-source code models. It supports multiple programming languages and is available in base, Python-specialized, and instruction-tuned variants.

Official Site 🤗 Hugging Face 📄 Research Paper

Input cost

Free (open source)

Output cost

Free (open source)

Context window

100K tokens

Max output

—

Modalities

text

Parameters

70B

License

Llama 2 Community License

Capabilities

Code GenerationCode CompletionCode DebuggingCode ExplanationMulti-language SupportInstruction FollowingPython Specialization (Code Llama - Python variant)

Best For

Code generation and understanding tasks, especially for developers seeking an open-source, high-performance code model.

Strengths

State-of-the-art performance among open-source code models
Supports a wide range of programming languages
Available in multiple variants (base, Python, instruct) for different use cases
Large 70B parameter scale for complex code reasoning

Limitations

Requires significant computational resources for inference
May generate insecure or buggy code if not carefully prompted
Not as capable as proprietary models like GPT-4 for nuanced code understanding
Limited to text modality; no vision or audio support

Use Cases

Automated code generation for software development

Code review and bug detection assistance

Educational tool for learning programming concepts

Code translation between programming languages

Documentation generation from code

Prototyping and rapid application development

Assisting with code refactoring and optimization

Improvements Over Previous Model

Larger parameter count (70B vs 34B) for better code reasoning
Improved performance on HumanEval and MBPP benchmarks
Extended context window from 16K to 100K tokens
Better multilingual code support
Instruction-tuned variant for improved following of code-related instructions

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