
Baseten has become a supported Inference Provider on the Hugging Face Hub, enhancing serverless AI capabilities for developers. This integration allows developers to access a variety of models, including popular LLMs like Kimi K3 and DeepSeek V4 Flash, directly through Hugging Face's platform. Users can choose to route requests via Hugging Face or use their own API keys, providing flexibility in billing. The integration is available through Hugging Face's SDKs for Python and JavaScript, making it easier for developers to incorporate AI into their applications.
Read originalThe b10311 release of llama.cpp tackles inefficiencies in text-to-speech (TTS) generation by refining how text streams are processed. Previously, the system would redundantly handle utterances, causing them to be read twice before completion. This update aligns the streaming overlay with the non-streaming prefill, effectively eliminating the duplication. Developers working with TTS systems will find this change streamlines the generation process and boosts efficiency. The update is accessible on macOS, Linux, and Windows, ensuring that a broad range of users can benefit from these improvements.
The b10313 release of llama.cpp introduces an LRU scheduler, significantly enhancing task management efficiency. This update includes improvements in handling coalescing, optimizing the waiting queue, and fixes for stream cases to ensure smoother operations. The release also expands platform-specific builds, such as Vulkan and ROCm 7.2 support on Ubuntu, and CUDA 12 and 13 on Windows. While there are no new model architectures, these updates demonstrate a commitment to refining performance and compatibility across various systems.