From 54501fe36bc54cf86363fcd8b9aeeb48fdb7e35d Mon Sep 17 00:00:00 2001 From: 0oshowero0 Date: Wed, 10 Jun 2026 09:44:17 +0800 Subject: [PATCH 1/2] update Signed-off-by: 0oshowero0 --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index b04a831..f3ca45b 100644 --- a/README.md +++ b/README.md @@ -31,6 +31,7 @@ TransferQueue offers **fine-grained, sub-sample-level** data management and **lo

🔄 Updates

+ - **June 10, 2026**: 🔥 TransferQueue has been adopted in [UniRL](https://github.com/Tencent-Hunyuan/UniRL), a unified RL framework for multimodal models developed by Tencent Hunyuan. - **April 15, 2026**: 🔥 TransferQueue has been adopted in [Relax](https://github.com/redai-infra/Relax)! By leveraging the `StreamingDataLoader` abstraction, it schedules training data across the cluster at micro-batch granularity, reducing synchronization barriers in a single-controller setup. - **April 10, 2026**: 🔥 TransferQueue is now officially integrated into [verl](https://github.com/verl-project/verl/pull/5401)! **We achieved an end-to-end performance gain of 49.1% for multi-modal post-training on a 128 × H100 GPU cluster!** Refer to [our blog](https://www.yuque.com/haomingzi-lfse7/lhp4el/gm8mkpfu83luuhxg?singleDoc#) for more details. - **Feb 8, 2026**: 🔥 Initialization and usage are greatly simplified by high-level APIs [PR#26](https://github.com/Ascend/TransferQueue/pull/26), [PR#28](https://github.com/Ascend/TransferQueue/pull/28). You can now use a Redis-style API to take advantage of most of the advanced features provided by TransferQueue! From 7d1891cdfb6155b24acf290dbf842707be27821f Mon Sep 17 00:00:00 2001 From: 0oshowero0 Date: Wed, 10 Jun 2026 09:44:29 +0800 Subject: [PATCH 2/2] update Signed-off-by: 0oshowero0 --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index f3ca45b..2bcfe41 100644 --- a/README.md +++ b/README.md @@ -31,7 +31,7 @@ TransferQueue offers **fine-grained, sub-sample-level** data management and **lo

🔄 Updates

- - **June 10, 2026**: 🔥 TransferQueue has been adopted in [UniRL](https://github.com/Tencent-Hunyuan/UniRL), a unified RL framework for multimodal models developed by Tencent Hunyuan. + - **June 9, 2026**: 🔥 TransferQueue has been adopted in [UniRL](https://github.com/Tencent-Hunyuan/UniRL), a unified RL framework for multimodal models developed by Tencent Hunyuan. - **April 15, 2026**: 🔥 TransferQueue has been adopted in [Relax](https://github.com/redai-infra/Relax)! By leveraging the `StreamingDataLoader` abstraction, it schedules training data across the cluster at micro-batch granularity, reducing synchronization barriers in a single-controller setup. - **April 10, 2026**: 🔥 TransferQueue is now officially integrated into [verl](https://github.com/verl-project/verl/pull/5401)! **We achieved an end-to-end performance gain of 49.1% for multi-modal post-training on a 128 × H100 GPU cluster!** Refer to [our blog](https://www.yuque.com/haomingzi-lfse7/lhp4el/gm8mkpfu83luuhxg?singleDoc#) for more details. - **Feb 8, 2026**: 🔥 Initialization and usage are greatly simplified by high-level APIs [PR#26](https://github.com/Ascend/TransferQueue/pull/26), [PR#28](https://github.com/Ascend/TransferQueue/pull/28). You can now use a Redis-style API to take advantage of most of the advanced features provided by TransferQueue!