
Meta introduces Code Llama 70B Open-Source AI Code Generation
Introduction
- Meta AI has released Code Llama 70B, an advanced version of its code generation model, designed to write code in various programming languages from natural language prompts or existing code snippets.
- This model represents a significant benchmark in the field of code generation, aiming to automate the process of creating and modifying software.
Technical Details
- Model Size and Training: Code Llama 70B is one of the largest open-source AI models for code generation, trained on 500 billion tokens of code and code-related data.
- Context Window: It features a larger context window of 100,000 tokens, enabling it to process and generate longer and more complex code sequences.
- Foundation: Based on Llama 2, a general-purpose large language model (LLM) with 175 billion parameters, Code Llama 70B has been fine-tuned for code generation using self-attention mechanisms.
Performance
- CodeLlama-70B-Instruct: A variant fine-tuned for understanding natural language instructions and generating code accordingly, scoring 67.8 on HumanEval, surpassing previous open models and comparable to closed models like GPT-4.
- CodeLlama-70B-Python: Optimized for Python, trained on an additional 100 billion tokens of Python code, enhancing its fluency and accuracy in generating Python code.
Accessibility
- Licensing: Available for free download under the same license as Llama 2, allowing both research and commercial use.
- Platforms and Frameworks: Accessible through platforms like Hugging Face, PyTorch, TensorFlow, and Jupyter Notebook, with documentation and tutorials provided by Meta AI.
Impact
- Software Development: Expected to significantly impact the field of code generation and software development by providing a powerful tool for creating and improving code.
- Learning and Accessibility: Lowers the barrier to entry for coding, offering guidance and feedback based on natural language instructions.
- New Applications: Enables new applications and use cases such as code translation, summarization, documentation, analysis, and debugging.
Conclusion
- Code Llama 70B is a groundbreaking open-source model that enhances the capabilities of AI in code generation, offering a versatile tool for developers and creating new opportunities for automation and efficiency in software development.
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The overwhelming demand for Nightshade momentarily overwhelmed the University of Chicago’s servers, prompting the addition of mirror links for easier access. This tool, alongside its predecessor Glaze—which aims to protect an artist’s unique style from being learned by AI by subtly altering images—forms part of The Glaze Project’s broader initiative to equip artists with defensive and offensive tools against AI exploitation. The project’s future plans include a combined tool that integrates the functionalities of both Glaze and Nightshade, although this is expected to undergo thorough testing before release. Despite the potential complexities of using both tools, the artist community has shown a willingness to adopt this layered approach for greater protection. The project’s leaders are considering releasing an open-source version of Nightshade, further democratizing access to these protective measures.
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The CEO of Mistral confirms the ‘leak’ of a new open-source AI model that approaches GPT-4 level performance
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Arthur Mensch, co-founder and CEO of Mistral, confirmed that an over-enthusiastic employee from one of their early access customers leaked a quantized and watermarked version of an old model they had openly distributed. This model was retrained from Llama 2 as soon as Mistral had access to its entire cluster, with the pretraining finishing on the day of Mistral 7B’s release. Despite the leak, Mensch’s comments suggest that Mistral is continuing to develop this model, potentially reaching or even surpassing GPT-4’s performance. This incident highlights the rapid advancements in open-source AI and the growing competition in the field, posing significant implications for the future of AI development and the balance of power among leading AI organizations.
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The introduction of these AI-powered capabilities signifies Shopify’s commitment to leveraging technology to enhance the merchant experience on its platform. By automating and optimizing tasks that traditionally required significant time and effort, Shopify aims to help merchants sell more effectively and create better customer experiences. The company’s focus on AI also positions it competitively against other major players in the commerce space, such as Adobe, Salesforce, and Oracle, who are similarly investing in AI to expand their capabilities. With these updates, Shopify continues to evolve its platform to meet the changing needs of merchants and consumers in the digital commerce landscape.
About The Author

Bogdan Iancu
Bogdan Iancu is a seasoned entrepreneur and strategic leader with over 25 years of experience in diverse industrial and commercial fields. His passion for AI, Machine Learning, and Generative AI is underpinned by a deep understanding of advanced calculus, enabling him to leverage these technologies to drive innovation and growth. As a Non-Executive Director, Bogdan brings a wealth of experience and a unique perspective to the boardroom, contributing to robust strategic decisions. With a proven track record of assisting clients worldwide, Bogdan is committed to harnessing the power of AI to transform businesses and create sustainable growth in the digital age.
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