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Description

OpenPipe offers an efficient platform for developers to fine-tune their models. It allows you to keep your datasets, models, and evaluations organized in a single location. You can train new models effortlessly with just a click. The system automatically logs all LLM requests and responses for easy reference. You can create datasets from the data you've captured, and even train multiple base models using the same dataset simultaneously. Our managed endpoints are designed to handle millions of requests seamlessly. Additionally, you can write evaluations and compare the outputs of different models side by side for better insights. A few simple lines of code can get you started; just swap out your Python or Javascript OpenAI SDK with an OpenPipe API key. Enhance the searchability of your data by using custom tags. Notably, smaller specialized models are significantly cheaper to operate compared to large multipurpose LLMs. Transitioning from prompts to models can be achieved in minutes instead of weeks. Our fine-tuned Mistral and Llama 2 models routinely exceed the performance of GPT-4-1106-Turbo, while also being more cost-effective. With a commitment to open-source, we provide access to many of the base models we utilize. When you fine-tune Mistral and Llama 2, you maintain ownership of your weights and can download them whenever needed. Embrace the future of model training and deployment with OpenPipe's comprehensive tools and features.

Description

Scale Evaluation presents an all-encompassing evaluation platform specifically designed for developers of large language models. This innovative platform tackles pressing issues in the field of AI model evaluation, including the limited availability of reliable and high-quality evaluation datasets as well as the inconsistency in model comparisons. By supplying exclusive evaluation sets that span a range of domains and capabilities, Scale guarantees precise model assessments while preventing overfitting. Its intuitive interface allows users to analyze and report on model performance effectively, promoting standardized evaluations that enable genuine comparisons. Furthermore, Scale benefits from a network of skilled human raters who provide trustworthy evaluations, bolstered by clear metrics and robust quality assurance processes. The platform also provides targeted evaluations utilizing customized sets that concentrate on particular model issues, thereby allowing for accurate enhancements through the incorporation of new training data. In this way, Scale Evaluation not only improves model efficacy but also contributes to the overall advancement of AI technology by fostering rigorous evaluation practices.