npx @buildinternet/releases get hugging-faceThe final v0 release adds a Parity-aware BPE implementation with an example and trainer API docs entry, and avoids a full vocab clone in get_vocab_size(). Maintainers note this is the last v0 release before moving to v1.
hf jobs scheduled ls now filters by --status, repeatable --label, and --name, matching hf jobs ls; the old -f/--filter flag is accepted but ignored with a warning and will be removed in a future release. ResolvedRevision now records the repo_id and repo_type it was resolved for, so re-resolving for the same repo returns as-is while different repos are resolved again.
Adds LowFormer, CPUBone, PP-LCNetV2, and LingBot-Vision model definitions with pretrained weights, plus per-batch and batch-size scheduling for non-NaFlex training with progressive resolution schedules. Improves NaFlexViT attention masks, position sampling, and fixes numerous small bugs in CutMix, optimizer paths, and checkpoint handling.
New chunked loss option for SFT reduces peak activation memory by processing tokens in checkpointed chunks, enabling longer sequences without OOM errors. Includes new DPO loss variant, OpenReward adapter, Cohere Cohere2 Gemma 3 Qwen3 Qwen2.5 chat templates; fixes CLI wildcard uploads and click 8.5 compatibility.
New pipelines include MiniMax-H3 (video+audio), MiniMax Music 3, Stable Audio 3, LTX-2.5, Wan-Animate-2, and JoyAI-Image-Edit-Plus. Modular Diffusers is no longer experimental, and minimal tensor-parallel support is added.
Fixed DFlash candidate token device mismatch with device_map='auto', aligned logit distributions for sampling-based candidate generators, fixed MTP config when mlp_layer_types is absent, and added a fallback from Lanczos to bicubic filtering on CUDA so images process on accelerator. Also fixed gemma4 video device placement.
The new hf endpoints hardware command lists valid hardware combinations with pricing and quota, mirrored in the SDK via list_inference_endpoints_hardware(). custom_image now accepts engine-specific container types (keyed by engine name) with new --engine, --tensor-parallel-size, and --data-parallel-size flags for deploy and update, while INFERENCE_ENDPOINT_IMAGE_KEYS is removed.
DistillationTrainer and DistillationConfig move from trl.experimental.distillation to the top-level trl package, with the old path emitting a FutureWarning until removal in v2.0.0. AsyncGRPOTrainer gains an experimental loop-owning path for training external agents like opencode, plus VLM support in DistillationTrainer and new DiffusionGemma SFT example.
Adds support for Meta's Muse Glimmer 30B multimodal model plus GraniteSWA, GraniteMoeSWA, A.X-K1/K2, and Cosmos3 Edge. Kernels for linear attention models (Mamba, GDN, Conv-only) are now opt-in rather than mandatory, cache cropping only accepts negative offsets, and T5 family gains SDPA support with a possible default attention change.
The hf-cli skill for AI agents is now installed globally by default by the standalone installers (bash and PowerShell), refreshed on hf update, with a once-daily hint if missing — silenced by HF_HUB_DISABLE_UPDATE_CHECK=1. --container-command and --container-args no longer require --custom-image for Inference Endpoints and can be changed after deploy via hf endpoints update; --health-route and --port still require a custom image. Baseten joins as an inference provider for the conversational task, plus a bucket prefix collision fix in HfFileSystem and a fix preventing double deletion of snapshot files.
The lerobot.types module was renamed to lerobot.lerobot_types. Additions include gradient checkpointing for diffusion models, slice support in LeRobotDataset, manual exposure/gain/white balance for RealSense cameras, private HF Hub dataset support, and a --no_stamp option for recording.
HfApi.resolve_revision and ResolvedRevision let libraries pin a revision once and guarantee all files come from the same commit. Two security fixes: downloads now reject absolute, UNC, and traversal filenames on all platforms, and the sandbox bootstrap no longer injects the HF token. Resource groups are now supported for Jobs and Collections, and the CLI surfaces job names as a first-class field.
PEFT v0.20.0 adds nine new methods including HiRA, GLoRA, BEFT, MonteCLoRA, VeLoRA, Uni-LoRA, FRoD, MiCA, and DEFT, along with automatic LoRA target selection, broader quantization support for BOFT, MiSS, VeRA, and SHiRA, and a new image generation benchmark. AutoGPTQ is formally deprecated following the switch to GPT-QModel.
Fixed a symlink-following arbitrary file write in archive extraction and a path traversal via metadata file_name in folder-based builders. Also fixed batch(by_column=...) crashing after shard/shuffle/split, CSV loader issues on pandas 2.0-2.2, and more than 20 other bugs across Arrow, JSON, and dataset card handling.