Yi-1.5: True Apache 2.0 Competitor to LLAMA-3

Prompt Engineering
13 May 202416:01

TLDRThe Yi-1.5 model family, developed by 01 AI, has recently been upgraded to surpass LLAMA-3 benchmarks and is released under the Apache 2.0 license, allowing for commercial use. The models, with varying parameter sizes of 6 billion, 9 billion, and 34 billion, have been trained on a massive scale and are capable of strong performance in coding, math reasoning, and instruction following. The 34 billion parameter model stands out for its close performance to the LLAMA 370 billion model. Despite a smaller context window of 4,000 tokens, the models demonstrate impressive reasoning and memory capabilities. They also show potential for application in various fields, including education and coding. The upcoming release of the Y-Large model is highly anticipated, promising further advancements in the field of large language models.

Takeaways

  • 🚀 The Yi-1.5 model family by 01 AI has significantly upgraded, now surpassing LLM benchmarks.
  • 📜 Yi-1.5 is released under the Apache 2.0 license, allowing for commercial use without restrictions.
  • 📈 Three model sizes are available: 6 billion, 9 billion, and 34 billion parameters, each offering different capabilities and hardware requirements.
  • 🧠 The 34 billion parameter model notably outperforms the LLAMA-3's 370 billion model in benchmarks.
  • 💡 Yi-1.5 demonstrates strong performance in coding, math reasoning, and instruction following.
  • 🔗 The 34 billion parameter model is accessible for testing on Hugging Face, with a link provided in the transcript.
  • 📱 The 6 billion parameter model is designed to potentially run on modern smartphones.
  • 🔢 Yi-1.5 shows good mathematical problem-solving skills and can perform basic calculations accurately.
  • 🤖 The model can understand and follow prompts, providing context-based responses and acknowledging instructions.
  • 🛠️ It has basic programming capabilities, able to identify and correct simple errors in code.
  • 🌐 Despite a limited context window of 4,000 tokens, the model is expected to expand this in future releases, potentially up to 200,000 tokens.
  • ⏳ The upcoming release of Yi-Large is anticipated to offer GP4-level performance, further enhancing the capabilities of the Yi-1.5 model family.

Q & A

  • What is the significance of the Yi-1.5 model family upgrade?

    -The Yi-1.5 model family upgrade is significant because it now surpasses Long benchmarks and is released under the Apache 2.0 license, allowing for commercial use without restrictions. It also extends the context window of an open language model to 200,000 tokens, which is a substantial improvement over previous models.

  • Which company developed the Yi model series?

    -The Yi model series is developed by 01 AI, a company based out of China.

  • What are the three different models released under the Yi-1.5 upgrade?

    -The three different models released under the Yi-1.5 upgrade are one with 6 billion parameters, another with 9 billion parameters, and the third with 34 billion parameters.

  • How many tokens were used for the fine-tuning of the Yi-1.5 models after the original pre-training?

    -The Yi-1.5 models were fine-tuned on 3 million samples after the original pre-training.

  • What is the current context window size for modern language models?

    -The current context window size for modern language models is 4,000 tokens.

  • What is the benchmark performance of the 34 billion parameter Yi-1.5 model?

    -The 34 billion parameter Yi-1.5 model performs closely or even outperforms the LLaMA 370 billion model, making it a standout in the release.

  • What are some of the capabilities that the Yi-1.5 model is said to deliver strong performance in?

    -The Yi-1.5 model is said to deliver strong performance in coding, math reasoning, and instruction following capabilities.

  • How can one test the 34 billion parameter Yi-1.5 model?

    -The 34 billion parameter Yi-1.5 model can be tested on Hugging Face, where a link to the model will be provided.

  • What is the limitation of the Yi-1.5 model in terms of context window size?

    -One of the limitations of the Yi-1.5 model is its limited context window size of 4,000 tokens.

  • What is the potential impact of the upcoming release of the Yi Large model?

    -The upcoming release of the Yi Large model is expected to be very exciting as it is anticipated to provide GP4 level capabilities, offering a strong competitor to existing models in the market.

  • How does the Yi-1.5 model handle requests involving illegal activities?

    -The Yi-1.5 model refuses to assist with requests involving illegal activities, instead providing educational or historical context when appropriate.

  • What is the Yi-1.5 model's approach to generating jokes about men or women?

    -The Yi-1.5 model generates jokes about men or women without outright denial, but the quality of the jokes is not necessarily high and they tend to vary a lot compared to other models.

Outlines

00:00

🚀 Introduction to the New Ye Model Series

The video introduces an upgraded version of the Ye model family developed by 01 AI, a Chinese company. These models are notable for their extended context window of 200,000 tokens and multimodal capabilities. The release includes three models with 6 billion, 9 billion, and 34 billion parameters, respectively, all of which are fine-tuned versions of the original Ye models. They are trained on 4.1 trillion tokens and 3 million samples. The video highlights the models' potential to expand their context window and their release under the Apache 2.0 license, allowing commercial use. The models are tested for their capabilities in various tasks, including ethical considerations, humor, and technical support.

05:01

🤔 Testing Ye Model's Reasoning and Deduction

The script details a series of tests to evaluate the Ye model's reasoning and deduction abilities. It includes questions about family relationships, item retention, and understanding instructions in mirror writing. The model demonstrates strong performance in logical reasoning, accurately answering family-related questions and making correct deductions about human behavior in given scenarios. However, it struggles with keeping track of multiple items in a sequence, similar to other models. The model also excels at understanding and responding to mirrored instructions, showcasing its ability to think through problems step by step.

10:01

🧮 Evaluating Mathematical and Coding Capabilities

The video assesses the Ye model's mathematical and coding skills. It correctly calculates probabilities and performs basic arithmetic operations. The model also retrieves information from context effectively and identifies errors in a provided Python program. Additionally, it attempts to write HTML code for a webpage with interactive elements but encounters issues with the random number generator for jokes. Despite this minor setback, the model shows promise in assisting with basic programming tasks and understanding simple code structures.

15:03

🌟 Conclusion on Ye Model's Performance and Potential

The video concludes by emphasizing the Ye model's impressive performance, especially considering its size. It notes the model's limitation of a 4,000 token context window but anticipates future improvements to match its 200,000 token capacity. The speaker recommends testing the model for applications, comparing it with other models like Llama 3 or Meena, and choosing based on specific application needs. The video also mentions the upcoming release of the Ye Large model and encourages viewers to stay tuned for further developments.

Mindmap

Keywords

💡Yi-1.5

Yi-1.5 refers to an upgraded model family developed by 01 AI, a company based in China. It is significant because it is a competitor to LLAMA-3 and is released under the Apache 2.0 license, allowing for commercial use. In the video, Yi-1.5 is highlighted for its ability to outperform benchmarks and extend the context window of an open language model to 200,000 tokens, which is a notable feature in the field of AI.

💡Apache 2.0

Apache 2.0 is an open-source software license that allows for commercial use, modification, and distribution of the software. In the context of the video, it is mentioned as a positive aspect of the Yi-1.5 model, as it enables users to utilize the model for commercial purposes without restrictions, which is a key selling point for developers and businesses looking to integrate AI models into their products.

💡Context Window

The context window refers to the amount of text or information that a language model can process at one time. In the video, it is mentioned that the Yi-1.5 model has a context window of 4,000 tokens, which is smaller than their previous models that could handle up to 200,000 tokens. The context window is crucial for the model's ability to understand and generate responses based on large amounts of context.

💡Multimodal Versions

Multimodal versions imply that the Yi-1.5 model has capabilities to process and understand multiple types of data or inputs, not just text. This is an advancement in AI as it allows the model to interact with the world in a more comprehensive way. The video discusses the Yi-1.5's multimodal capabilities, suggesting that it can handle different forms of data, which enhances its versatility and applicability in various AI applications.

💡Benchmarks

Benchmarks are a set of tests or comparisons used to evaluate the performance of a system, in this case, the Yi-1.5 model. The video script mentions that the Yi-1.5 model is beating benchmarks, which means it is outperforming other models in its class based on standardized tests. This is an important metric for demonstrating the effectiveness of the model.

💡Parameter

In machine learning, a parameter is a variable that is learned from data and used to make predictions or decisions. The video discusses different versions of the Yi-1.5 model, which vary in the number of parameters they have, such as 6 billion, 9 billion, and 34 billion parameters. The number of parameters often correlates with the complexity a model can handle and its performance capabilities.

💡Hugging Face

Hugging Face is a platform that provides tools and libraries for natural language processing (NLP). In the video, it is mentioned as a place where the 34 billion parameter version of the Yi-1.5 model is available for testing. This indicates that users can access and experiment with the model through this platform to evaluate its capabilities.

💡Gradio

Gradio is an open-source Python library used for quickly creating web demos for machine learning models. The video script describes using Gradio to test the Yi-1.5 model, which suggests that it is a user-friendly tool for interfacing with AI models and obtaining real-time feedback on their performance.

💡Quantized Version

A quantized version of a model refers to a model that has undergone quantization, a process that reduces the precision of the model's parameters to use less computational resources. The video mentions that if one uses the quantized version of the Yi-1.5 model, they might see slightly different results, indicating that the quantization process can affect the model's output.

💡Math Reasoning

Math reasoning is the ability to understand and deduce conclusions based on mathematical principles. The video highlights that the Yi-1.5 model delivers strong performance in math reasoning, which is demonstrated through its ability to solve mathematical problems and follow logical steps to reach correct answers.

💡Instruction Following Capabilities

Instruction following capabilities refer to the model's ability to understand and act upon a series of commands or instructions. The video tests this by providing prompts and checking if the model can respond accurately. This is an important aspect for AI models as it demonstrates their utility in executing tasks as directed by users.

Highlights

The Yi-1.5 model family, developed by 01 AI, has achieved significant upgrades and is now outperforming LLAMA-3 benchmarks.

Yi-1.5 models are released under the Apache 2.0 license, allowing for commercial use without restrictions.

The Yi-1.5 series includes three models with 6 billion, 9 billion, and 34 billion parameters, respectively.

The 34 billion parameter model reportedly outperforms the original GP4 and is close to the performance of the LLAMA 370 billion model.

Yi-1.5 models demonstrate strong performance in coding, math reasoning, and instruction following capabilities.

The 6 billion parameter model is designed to potentially run on modern smartphones.

The context window for Yi-1.5 models is currently 4,000 tokens, but the company has experience with models that extend to 100,000 tokens.

The 9 billion parameter model outperforms all other models in its class based on benchmarks.

The Yi-1.5 models are available on Hugging Face for testing.

The model's ethical stance prevents it from assisting with illegal activities, even when rephrased for educational purposes.

The model can generate jokes, albeit not of the highest quality, and does not outright deny such requests.

Yi-1.5 models can answer technical questions without hesitation, such as how to kill a Linux process.

The model demonstrates good reasoning abilities, remembering context from previous interactions.

In logical deduction tasks, the model can make accurate inferences based on provided scenarios.

The model struggles with keeping track of multiple items in a sequence, similar to other models.

The 34 billion parameter model excels at understanding and responding to mirrored text instructions.

Yi-1.5 models show basic mathematical understanding and can perform simple calculations correctly.

The model can retrieve and provide information based on a given context, suitable for reference and assistance tasks.

Yi-1.5 models can identify errors in provided Python code and assist with corrections.

The model is capable of generating HTML code for a web page with interactive elements.

Despite a limited context window, the Yi-1.5 model shows potential for expansion and improved performance in future releases.

The upcoming release of the Yi Large model is anticipated to provide GP4-level capabilities.

For those building LLM-based applications, it is recommended to test the Yi-1.5 model alongside LLAMA-3 and MILE to determine the best fit.