Phind's Groundbreaking Generative AI Model ‘V7’ Exceeds OpenAI’s GPT-4 in Coding Skills
In Brief
Phind has made strides in AI-driven coding with its latest seventh-generation model, praised for its ability to outperform the coding abilities typically seen in GPT-4.
In the dynamic realm of AI and coding, Phind recently introduced The latest model, regarded for not just matching but also surpassing the esteemed coding capabilities of GPT-4, has become a topic of discussion.
The Phind Model V7 This new model is creating quite a buzz, showcasing an exceptional speed that is five times quicker than its predecessor, shortening response times from 50 to just 10 seconds for technical inquiries.
Capitalizing on the successes of the open-source CodeLlama-34B fine-tunes, the Phind team has developed a trailblazing model that has set the mark by being the first to exceed previous benchmarks. GPT-4 in the HumanEval benchmark.
Standing at a 74.7% pass on HumanEval The model takes advantage of a vast fine-tuning process that encompasses over 70 billion tokens of top-tier code and problem-solving materials. Nonetheless, Phind acknowledges that the HumanEval score does not entirely capture practical applicability, a point further supported by in-depth user feedback and the model's impressive performance in authentic coding scenarios.
Our coding model, which surpasses GPT-4 in capabilities, is now the standard on https://t.co/epkoFW8Ozz .
— Phind (@phindsearch) October 31, 2023
It's also 5x faster than GPT-4.
Learn more in our blog post: https://t.co/PrOFETEbvd
Phind's Community Tech Support
Within the Phind Discord community, members have shown a clear preference for the new model over GPT-4, even when they have unrestricted access to both models. The team has remarkably enhanced speed through the use of NVIDIA's TensorRT-LLM library on H100s hardware, managing an impressive rate of 100 tokens per second in a single stream.
In terms of contextual capacity, Phind has expanded its token support up to 16,000, allowing developers a broader scope, with 12,000 tokens allocated for input and an additional 4,000 reserved for web-based results. This increased token capacity enables a deeper understanding and generation of intricate code.
Continuous Improvements to Address Challenges
While Phind takes pride in the accomplishments of its new model, it recognizes that some inconsistencies remain. The team is dedicated to ongoing enhancements to bolster reliability, especially for more complex queries that may require multiple attempts to arrive at the correct answer.
Phind’s groundbreaking model is now readily available for users to explore on their website, offering unlimited free uses, reflecting their mission to democratize AI-powered coding assistance. In addition to code generation, Phind delivers a virtual pair programming environment, allowing developers to collaborate and streamline their coding efforts.
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