Yi-Coder : The BEST SMALL & Opensource CODING LLM is here! (Beats DeepSeek, Qwen & Others)
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In this video, I'll be fully testing the New Yi-Coder Models (1.5B, 9B) to check if it's really good. I'll also be trying to find out if it can really beat Llama-3.1, Claude 3.5 Sonnet, GPT-4O, DeepSeek & Qwen-2 in coding tests. Yi-Coder model is fully opensource and can be used for FREE. Yi-Coder is even better in Coding Tasks and is also really good at doing Text-To-Application, Text-To-Frontend and other things as well. I'll be testing it to find out if it can really beat other LLMs and i'll also be telling you that how you can use it.
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Key Takeaways:
🔥 Yi-Coder Models Launched: Discover the new open-source coding models from Yi-Coder, featuring powerful AI coding tools with fewer than 10 billion parameters.
💻 Two Coding-Specific Models: Yi-Coder introduces a 9 billion parameter model and a lightweight 1.5 billion model, both perfect for coding on any computer!
🚀 Outperforms Competition: Yi-Coder-9B surpasses top models like CodeQwen 7B, CodeGeex 9B, and even rivals DeepSeek-Coder 33B in benchmark results.
🔍 128K Token Context Window: The large context window enables project-level code comprehension, making these models ideal for handling large-scale coding projects.
📊 Live Benchmark Results: Yi-Coder beats major models in Live Code, MBPP, CRUXEval, and more, setting new standards in AI-powered code generation.
🎯 Performance on Autocompletion: The 1.5b model excels at autocompletion and basic coding tasks, even on simple computers. Ideal for developers looking for quick and efficient code suggestions.
📈 Practical Testing: See how these models perform in real-world coding challenges like HTML, Python, and JS tasks, showing their strengths and limitations.
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Timestamps:
00:00 - Introduction
00:08 - About New Yi-Coder Models
03:08 - Testing
06:57 - Conclusion
07:49 - Ending
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