Use scalable annotation runtime, shared human-video module and optional Flora captions
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README.md
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Enter a LeRobot v3 dataset, choose annotations, review an estimate, then sign in
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with Hugging Face to run a
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Jobs and inference are billed to the signed-in user's personal account.
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The Space itself uses free CPU hardware and has no shared HF access token.
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image edits, spending/time guards and the media viewer. End-frame editing remains
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available in the CLI but is not included in the Studio's single-edit quote.
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In **Model
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the intervals generated by
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boundaries; the relabeled subtasks then feed plans, memory and human videos.
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It uses NVIDIA's pinned native frame planner, video processor, mixed BF16/FP32
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loader and greedy decoder with BEFORE/TARGET/AFTER context. The input uses the
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Flora has no hosted Inference Provider route. Selecting it runs the worker on an
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H200 CUDA Job; the quote reserves the entire GPU timeout, including installation,
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weight downloads and startup. Other annotations
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Inference Providers. The default keeps the CPU workflow.
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[Flora's model card](https://huggingface.co/nvidia/Flora-Captioner) limits use to
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noncommercial research. Code and weight revisions are pinned in `flora_captioner.py`
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and each run manifest. This option is experimental
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The default **tuned Qwen3.8** preset uses the action-phase prompt developed on
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ABC, timestamped contact sheets at 2 fps, 1,200 frames per request, and up to
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Enter a LeRobot v3 dataset, choose annotations, review an estimate, then sign in
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with Hugging Face to run a Job using the selected annotation model. General vision
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models use a CPU Job and Inference Providers; Flora uses an H200 GPU Job.
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Jobs and inference are billed to the signed-in user's personal account.
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The Space itself uses free CPU hardware and has no shared HF access token.
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| 45 |
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| 63 |
image edits, spending/time guards and the media viewer. End-frame editing remains
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available in the CLI but is not included in the Studio's single-edit quote.
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In the **Model** selector, choose **NVIDIA Flora-Captioner** to relabel
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the intervals generated by its Qwen3.8 27B helper. The helper is shown beneath
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the selector and in the review, with its provider rates. Flora preserves those
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boundaries; the relabeled subtasks then feed plans, memory and human videos.
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It uses NVIDIA's pinned native frame planner, video processor, mixed BF16/FP32
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loader and greedy decoder with BEFORE/TARGET/AFTER context. The input uses the
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| 74 |
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Flora has no hosted Inference Provider route. Selecting it runs the worker on an
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| 76 |
H200 CUDA Job; the quote reserves the entire GPU timeout, including installation,
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| 77 |
+
weight downloads and startup. Other annotations use the helper VLM through
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Inference Providers. The default keeps the CPU workflow.
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[Flora's model card](https://huggingface.co/nvidia/Flora-Captioner) limits use to
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noncommercial research. Code and weight revisions are pinned in `flora_captioner.py`
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and each run manifest. This option is experimental. `benchmark_flora.py` supports
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a paired 25-episode ABC captioning comparison separately from boundary detection.
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The default **tuned Qwen3.8** preset uses the action-phase prompt developed on
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ABC, timestamped contact sheets at 2 fps, 1,200 frames per request, and up to
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