hfl is a Python package that enables running Hugging Face models locally, similar to Ollama. It supports GGUF, Llama.cpp, MLX, and provides an OpenAI-compatible API for self-hosted inference. Licensed under Apache-2.0, it is designed for developers who want to serve LLMs on their own hardware.
hfl sits in PulseGate's Other AI category. It focuses on running Hugging Face models locally on your own machine without relying on cloud services. It is built as an open-source project for developers. hfl is open source under the Apache-2.0 license. hfl is available on the command line and API, and it can be self-hosted.
It is developed by ggalancs, and the product first shipped in 2026. Development happens publicly on GitHub with 145 commits in the last 90 days. Key capabilities include Local Inference, GGUF Support, and OpenAI Compatible API. It exposes integrations via a public API.
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