InferenceClient

This release enhances the `hf-cli` skill by enabling automatic installation and synchronization, introduces flexible engine flag management for Inference Endpoints, and adds Baseten as a new inference provider. It also includes several quality-of-life improvements and bug fixes.

This release introduces significant new CLI functionality for managing Spaces, Discussions, Webhooks, and Datasets, alongside major enhancements to file system support with the addition of Bucket integration in HfFileSystem and pip installable CLI extensions.

This release introduces major new capabilities including S3-like Buckets for large object storage and a powerful CLI Extension system. It also brings significant usability improvements to the CLI, especially around Jobs management and AI Agent support.

This release introduces new parameters to the InferenceClient for controlling output embedding size, enhancing its flexibility for embedding-related tasks.

This release introduces OVHcloud AI Endpoints as a new Inference Provider and significantly speeds up CLI installation by integrating `uv` support. Several minor bug fixes address issues in collections, CLI debugging, and inference parsing.

This release focuses on optimizing the file download experience through multi-threading and cleaner CLI output, while significantly expanding CLI capabilities with new commands for managing Inference Endpoints and verifying cache integrity. New support for WaveSpeedAI and image segmentation on fal are also introduced.

This release introduces Z.ai as a new official Inference Provider on the Hub and includes an optimization for file system glob operations.

This release introduces PublicAI as a new supported inference provider, allowing users to interact with models hosted by this nonprofit organization via InferenceClient.

This release introduces Scaleway as a new supported inference provider, allowing users to access models hosted on their infrastructure via the InferenceClient.

This release introduces 'Jobs', a powerful new CLI and Python API for running compute tasks on Hugging Face infrastructure using Docker-like commands. Additionally, the Hugging Face CLI has been officially renamed from `huggingface-cli` to `hf`, and the InferenceClient gained image-to-image support.

This release introduces two major new inference providers, Featherless.AI and Groq, significantly enhancing model accessibility and inference speed. It also brings several quality-of-life improvements, bug fixes across various components, and advancements for local agent execution via MCP and tiny-agents.

This release introduces powerful new capabilities for LLM interaction via the Model Context Protocol (MCP) Client and Tiny Agents CLI, alongside support for new inference providers and enhanced dataclass validation with the @strict decorator.

This release introduces major enhancements to Inference Providers, adding support for LoRA inference via fal.ai and Replicate, and enabling 'auto' provider selection as the new default. Additionally, Xet uploads now support byte arrays, and large file downloads (>50GB) are more reliable.

This patch release addresses several bugs related to the InferenceClient, specifically fixing text-generation with external providers and conversational handling in HfInference.

This major release introduces Xet, a new protocol for storing large objects in Git, and significantly enhances the InferenceClient with new providers (Cerebras, Cohere, Novita) and organizational billing support. New features also include wildcard support for CLI uploads and programmatic LFS file management.

This release introduces major updates to the InferenceClient, enabling unified inference across multiple third-party providers using Hugging Face Hub model IDs. Additionally, HfApi has been updated with new repository properties and the deprecated `like` endpoint has been removed.