Core features
No-code fine-tuning
NLP practitioners can easily fine-tune models without the need for code expertise. The user interface, which is specifically designed for LLMs, allows users to upload large datasets easily and configure hyperparameters to fine-tune the model.
Highly customizable (wide range of hyperparameters)
H2O LLM Studio supports a wide variety of hyperparameters that can be used to fine-tune the model and supports the following fine-tuning techniques to enable advanced customization:
Advanced evaluation metrics and experiment comparison
Advanced evaluation metrics in H2O LLM Studio can be used to validate the answers generated by the LLM. This helps to make data-driven decisions about the model. It also offers visual tracking and comparison of experiment performance, making it easy to analyze and compare different fine-tuned models.You can also visualize how different parameters affect the model performance, and optionally use the Neptune integration to track and log your experiments.
Instant publishing models
H2O LLM Studio enables easy model sharing with the community by allowing you to export the model to the Hugging Face Hub with a single click.
Instant feedback on model performance
Additionally, H2O LLM Studio lets you chat with the fine-tuned model and receive instant feedback about model performance.
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