Forefront

What is Forefront?

Forefront is a platform for building with open-source AI models, designed to feel familiar to users of closed-source platforms. It offers fine-tuning with your own data, model evaluation, training monitoring, and easy imports from HuggingFace. A built-in AI data warehouse stores training, validation, and evaluation data, giving teams a single source for their AI datasets, while cross-department collaboration is designed to speed up decision-making.

Who created Forefront?

Forefront was built by a team of developers who wanted a better way to build and fine-tune open-source AI models. The platform emphasizes control, transparency, and the flexibility to fine-tune models for specific needs, reflecting the team’s belief in owning your AI models and supporting open AI innovation.

What is Forefront used for?

• Fine-tuning: Fine-tune models for a wide range of tasks and find the best starting model for your use case, using ready-to-use datasets or your own training and validation data.
• Deployment: Run models via API servers and serverless inference endpoints for every model, with integration requiring about three lines of code. You can also experiment in the Playground or export models to host yourself or with another provider.
• Monitoring and evaluation: Track training with built-in loss charts and run automated evaluations against a validation set via API.
• Data analysis: Analyze data distribution, spot patterns, and identify imbalances or biases. The Inspector tool simplifies data navigation, and storing production data builds a data advantage for future fine-tuning.
• Collaboration: Work together through group and individual chats, with chat and completion endpoints for real-time text conversations. The ‘My Account’ portal manages account details and settings.

Who is Forefront for?

Forefront suits developers, data scientists, analysts, researchers, startups, and enterprises working with open-source AI models.