Instructions to use Apryle/AVTime-RL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apryle/AVTime-RL with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Apryle/AVTime-RL") model = AutoModelForMultimodalLM.from_pretrained("Apryle/AVTime-RL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
AVTime-RL
AVTime-RL-BiTSC-GRPO-v1 is a merged, bf16 milestone for time-aware
audio-video understanding. It starts from Qwen/Qwen3-Omni-30B-A3B-Instruct,
uses one-round AVTime/LongVALE supervision, and is then optimized with
multi-task GRPO for timestamped dense video captioning, temporal video
grounding, and segment captioning.
Milestone identity
| Field | Value |
|---|---|
| Release | AVTime-RL-BiTSC-GRPO-v1 |
| Checkpoint | merged checkpoint 60 |
| Precision | bfloat16 |
| Serialization | 15 safetensors shards, about 66 GB total |
| Architecture | Qwen3OmniMoeForConditionalGeneration |
| Release date | 2026-08-11 |
This is a fully merged checkpoint; no LoRA adapter needs to be applied at
inference time. Use a recent transformers or vLLM build that supports
Qwen3-Omni MoE models and provide both video and audio when available.
Training
The GRPO mixture contains 12,484 examples: 70.0% dense video captioning (DVC), 15.0% temporal video grounding (TVG), and 15.0% segment captioning (SC). It combines 7,239 LongVALE DVC examples, 1,500 AVTime DVC examples, 1,872 LongVALE TVG examples, and 1,873 LongVALE SC examples.
The main DVC reward is BiTSC (bidirectional time-semantic consistency): a local RLAIF judge matches captions to events, while deterministic code measures the resulting temporal overlap in both Time-to-Event and Event-to-Time directions. TVG uses official-format parsing plus temporal IoU and boundary proximity; SC uses deterministic lexical coverage and length calibration.
LongVALE evaluation
The following results use the LongVALE test split (1,171 videos and 13,867 events) and the official metric implementation.
| Task | Metric | Score |
|---|---|---|
| Omni-TVG | R@0.3 | 26.13 |
| Omni-TVG | R@0.5 | 16.85 |
| Omni-TVG | R@0.7 | 8.71 |
| Omni-TVG | mIoU | 17.76 |
| Omni-SC | BLEU-4 | 7.79 |
| Omni-SC | ROUGE-L | 24.84 |
| Omni-SC | CIDEr | 31.28 |
| Omni-SC | METEOR | 13.20 |
On the clean 512-video DVC evaluation using the historical one-round generation protocol, the model achieves SODA-C 5.057, METEOR 7.033, and CIDEr 12.156.
For TVG, evaluation used constrained decoding to enforce LongVALE's official
From XX to YY response syntax. Fair comparisons should use the same output
constraint for every compared model; this checkpoint should not be interpreted
as a claim about unconstrained free-form timestamp formatting.
Limitations and use
This is a research checkpoint, not a safety-validated production system. Its timestamps and captions can be inaccurate, especially for subtle audio events, very long videos, or videos outside the training distribution. The checkpoint does not include any LongVALE or AVTime media or annotations. Users must comply with the terms of the upstream base model and any input datasets.
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Base model
Qwen/Qwen3-Omni-30B-A3B-Instruct