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OPTIMUM-INTEL ADDS META MUSE GLIMMER SUPPORT VIA OPENVINO
By RepoJournal · Filed · About Hugging Face
OpenVINO now exports Meta's Muse Glimmer multimodal model with int4 quantization, bringing image-text-to-text inference to the optimization stack.
The Optimum Intel team landed full support for Meta Muse Glimmer [1], including both Onyx and Glimmer variants, with floating-point attention masks in the vision encoder and video support [2]. The PR adds quantization-aware export paths, integration tests, and documentation for a model that handles vision and language in tandem. Elsewhere, FunASR model type handling got corrected [3] to align with OpenVINO's type expectations. On the Hub side, the CLI's scheduled upload feature had a critical bug: `hf upload <repo> <dir>/<file> --every N` never committed anything because the command passed the full local path as an allow pattern, but CommitScheduler matches patterns against folder-relative paths [4]. That's fixed. Documentation work shipped across hub-docs, including OAuth scope clarification for Inference Endpoints [5] and a corrected import example for parse_hf_mount [6].
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Action items
- → Test Muse Glimmer exports in your pipelines if you rely on multimodal quantization huggingface/optimum-intel [plan]
- → Update if you use `hf upload --every` for single files in subdirectories huggingface/huggingface_hub [immediate]
- → Check the new Inference Endpoints OAuth scopes documentation if you manage Hub integrations huggingface/hub-docs [monitor]
References
- [1] [OpenVINO] Support Meta Muse Glimmer ↗ huggingface/optimum-intel
- [2] [OpenVINO] Support Meta Muse Glimmer (#1924) huggingface/optimum-intel
- [3] Fix model type for FunASR. (#1925) huggingface/optimum-intel
- [4] [CLI] Fix scheduled upload of a single file in a subfolder (#4619) huggingface/huggingface_hub
- [5] Document read-endpoints / write-endpoints OAuth scopes ↗ huggingface/hub-docs
- [6] Fix import path in parse_hf_mount doc example (#4621) huggingface/huggingface_hub