Enterprise Growth Optimization Specialist

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Support for long text: The support for long text context length is twice that of 100000. Instruction fine-tuning: Improvements in the post-training process have greatly reduced the model error rate, further improved consistency and increased the diversity of model responses. Training efficiency: The training efficiency is times higher than . New capabilities: It has enhanced reasoning and code capabilities, can perform complex reasoning, can follow instructions more easily, can visualize ideas and solve many subtle problems, and also supports zero-shot tool use, including web search, mathematical operations and code execution. Through fine-tuning, it provides strong flexibility in calling custom tools. Version open source: Two small parameter versions of 100 million () and 100 million () have been opened for pre-training and fine-tuning, and are open to developers, including pre-training and fine-tuning versions.


It said that the largest model under development is + parameters and poland whatsapp resource a multimodal version will be launched in the next few months. Wide application: It can be used to upgrade the tool and will be integrated into the search function of major platforms such as , , and . The model will also be provided to developers on Amazon, , Google Cloud, , , , Microsoft Cloud z, NVIDIA and , and will be supported by hardware platforms provided by , , Dell, Intel, NVIDIA and Qualcomm. A new set of high-quality human evaluation datasets has also been developed to cover key use cases to evaluate model performance.


In addition, to maintain its leading position in open source, it has relaxed the license for the first time to allow developers to use the high-quality output of the model to improve and develop third-party NVIDIA models. It was released on January 2, 2017, surpassing NVIDIA and NVIDIA in multiple benchmarks. The performance of the version is comparable to that of the best closed-source models. It supports contexts with multi-language capabilities (including English, German, French, Italian, Portuguese, Hindi, Spanish and Thai), good code generation capabilities, complex reasoning capabilities, and tool usage capabilities. At the same time, it generously released a multi-page paper that detailed pre-training data, filtering, annealing, synthetic data, scaling laws, infrastructure, parallel processing, training methods, post-training adaptation, tool usage, benchmarks, reasoning strategies, quantization, vision, speech and video.