The latest release of watsonx.ai includes the following features and updates:

Bring your own foundation model to inference from watsonx.ai
In addition to working with foundation models that are curated by IBM, you can now upload and deploy your own foundational models. After the models are deployed and registered with watsonx.ai, create prompts that inference the custom models from the Prompt Lab. To learn more about uploading custom foundation models, see Deploying custom foundation models. Also described is a list of supported GPU configurations, model architectures, and suggested matching hardware configurations.

The watsonx.ai API is available for use
You can now programmatically work with foundation models that are hosted in watsonx.ai by calling the watsonx.ai API directly. For more information, see the watsonx.ai API reference documentation.

Prompt-tune the llama-2-13b-chat foundation model
The Tuning Studio now supports tuning the llama-2-13b-chat foundation model. Start by engineering prompts for the larger llama-2-70b-chat model in the Prompt Lab to find effective prompt inputs for your use case. Then tune the smaller version of the Llama 2 model to generate comparable or better outputs with zero-shot prompts. For more information, see Tuning Studio.

A modification to the granite-13b-chat-v2 foundation model is available
The latest version of the granite-13b-chat-v2 is 2.1.0. The modification includes improvements that were gained by applying a novel AI alignment technique to the version 2.0.0 model. AI alignment involves using fine-tuning and reinforcement learning techniques to guide the model to return outputs that are as helpful, truthful, and transparent as possible. For more information, see the What is AI alignment? blog post from IBM Research.

More foundation models are available
The following foundation models are now available for inferencing from the Prompt Lab in watsonx.ai:

• granite-8b-japanese: A foundation model from the IBM Granite family that is trained to understand and generate Japanese text. You can use the granite-8b-japanese foundation model for general purpose tasks in the Japanese language, such as classification, extraction, question-answering, and for language translation between Japanese and English.
• granite-20b-multilingual: A foundation model from the IBM Granite family that is trained for translation tasks in English, German, Spanish, French, and Portuguese.
• codellama-34b-instruct: A programmatic code generation model from Code Llama that is based on Llama 2 from Meta. Use Code Llama to create prompts for generating code based on natural language inputs, and for completing and debugging code.
• mixtral-8x7b-instruct-v01-q: A version of the Mixtral 8x7B Instruct foundation model from Mistral AI that is quanitzed by IBM. You can use this new model for general-purpose tasks, including classification, summarization, code generation, language translation, and more.

For more information, see Supported foundation models.

Nick