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Posted to commits@texera.apache.org by gi...@apache.org on 2026/07/03 03:23:33 UTC
(texera) branch gh-readonly-queue/main/pr-6067-0535b16cfff48a5d247a84ff58c0255b959e2923 created (now 6364dfa72e)
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at 6364dfa72e chore(deps): bump transformers from 5.0.0rc3 to 5.3.0 in /amber (#6067)
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(texera) 01/01: chore(deps): bump transformers from 5.0.0rc3 to 5.3.0 in /amber (#6067)
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github-merge-queue[bot] pushed a commit to branch gh-readonly-queue/main/pr-6067-0535b16cfff48a5d247a84ff58c0255b959e2923
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commit 6364dfa72eb2df8e4443ec7d07ff7bf1bcd6a58b
Author: dependabot[bot] <49...@users.noreply.github.com>
AuthorDate: Thu Jul 2 20:23:12 2026 -0700
chore(deps): bump transformers from 5.0.0rc3 to 5.3.0 in /amber (#6067)
Bumps [transformers](https://github.com/huggingface/transformers) from
5.0.0rc3 to 5.3.0.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/huggingface/transformers/releases">transformers's
releases</a>.</em></p>
<blockquote>
<h2>v5.1.0: EXAONE-MoE, PP-DocLayoutV3, Youtu-LLM, GLM-OCR</h2>
<h2>New Model additions</h2>
<h3>EXAONE-MoE</h3>
<!-- raw HTML omitted -->
<p>K-EXAONE is a large-scale multilingual language model developed by LG
AI Research. Built using a Mixture-of-Experts architecture, K-EXAONE
features 236 billion total parameters, with 23 billion active during
inference. Performance evaluations across various benchmarks demonstrate
that K-EXAONE excels in reasoning, agentic capabilities, general
knowledge, multilingual understanding, and long-context processing.</p>
<ul>
<li>Add EXAONE-MoE implementations (<a
href="https://redirect.github.com/huggingface/transformers/issues/43080">#43080</a>)
by <a href="https://github.com/nuxlear"><code>@nuxlear</code></a></li>
</ul>
<h3>PP-DocLayoutV3</h3>
<!-- raw HTML omitted -->
<p><strong>PP-DocLayoutV3</strong> is a unified and high-efficiency
model designed for comprehensive layout analysis. It addresses the
challenges of complex physical distortions—such as skewing, curving, and
adverse lighting—by integrating instance segmentation and reading order
prediction into a single, end-to-end framework.</p>
<ul>
<li>[Model] Add PP-DocLayoutV3 Model Support (<a
href="https://redirect.github.com/huggingface/transformers/issues/43098">#43098</a>)
by <a
href="https://github.com/zhang-prog"><code>@zhang-prog</code></a></li>
</ul>
<h3>Youtu-LLM</h3>
<!-- raw HTML omitted -->
<p>Youtu-LLM is a new, small, yet powerful LLM, contains only 1.96B
parameters, supports 128k long context, and has native agentic talents.
On general evaluations, Youtu-LLM significantly outperforms SOTA LLMs of
similar size in terms of Commonsense, STEM, Coding and Long Context
capabilities; in agent-related testing, Youtu-LLM surpasses larger-sized
leaders and is truly capable of completing multiple end2end agent
tasks.</p>
<ul>
<li>Add Youtu-LLM model (<a
href="https://redirect.github.com/huggingface/transformers/issues/43166">#43166</a>)
by <a href="https://github.com/LuJunru"><code>@LuJunru</code></a></li>
</ul>
<h3>GlmOcr</h3>
<!-- raw HTML omitted -->
<p>GLM-OCR is a multimodal OCR model for complex document understanding,
built on the GLM-V encoder–decoder architecture. It introduces
Multi-Token Prediction (MTP) loss and stable full-task reinforcement
learning to improve training efficiency, recognition accuracy, and
generalization. The model integrates the CogViT visual encoder
pre-trained on large-scale image–text data, a lightweight cross-modal
connector with efficient token downsampling, and a GLM-0.5B language
decoder. Combined with a two-stage pipeline of layout analysis and
parallel recognition based on PP-DocLayout-V3, GLM-OCR delivers robust
and high-quality OCR performance across diverse document layouts.</p>
<ul>
<li>[GLM-OCR] GLM-OCR Support (<a
href="https://redirect.github.com/huggingface/transformers/issues/43391">#43391</a>)by
<a
href="https://github.com/zRzRzRzRzRzRzR"><code>@zRzRzRzRzRzRzR</code></a></li>
</ul>
<h2>Breaking changes</h2>
<ul>
<li>
<p>🚨 T5Gemma2 model structure (<a
href="https://redirect.github.com/huggingface/transformers/issues/43633">#43633</a>)
- Makes sure that the attn implementation is set to all sub-configs. The
config.encoder.text_config was not getting its attn set because we
aren't passing it to PreTrainedModel.<strong>init</strong>. We can't
change the model structure without breaking so I manually re-added a
call to self.adjust_attn_implemetation in modeling code</p>
</li>
<li>
<p>🚨 Generation cache preparation (<a
href="https://redirect.github.com/huggingface/transformers/issues/43679">#43679</a>)
- Refactors cache initialization in generation to ensure sliding window
configurations are now properly respected. Previously, some models (like
Afmoe) created caches without passing the model config, causing sliding
window limits to be ignored. This is breaking because models with
sliding window attention will now enforce their window size limits
during generation, which may change generation behavior or require
adjusting sequence lengths in existing code.</p>
</li>
<li>
<p>🚨 Delete duplicate code in backbone utils (<a
href="https://redirect.github.com/huggingface/transformers/issues/43323">#43323</a>)
- This PR cleans up backbone utilities. Specifically, we have currently
5 different config attr to decide which backbone to load, most of which
can be merged into one and seem redundant
After this PR, we'll have only one config.backbone_config as a single
source of truth. The models will load the backbone from_config and load
pretrained weights only if the checkpoint has any weights saved. The
overall idea is same as in other composite models. A few config
arguments are removed as a result.</p>
</li>
<li>
<p>🚨 Refactor DETR to updated standards (<a
href="https://redirect.github.com/huggingface/transformers/issues/41549">#41549</a>)
- standardizes the DETR model to be closer to other vision models in the
library.</p>
</li>
<li>
<p>🚨Fix floating-point precision in JanusImageProcessor resize (<a
href="https://redirect.github.com/huggingface/transformers/issues/43187">#43187</a>)
- replaces an <code>int()</code> with <code>round()</code>, expect light
numerical differences</p>
</li>
<li>
<p>🚨 Remove deprecated AnnotionFormat (<a
href="https://redirect.github.com/huggingface/transformers/issues/42983">#42983</a>)
- removes a missnamed class in favour of
<code>AnnotationFormat</code>.</p>
</li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="https://github.com/huggingface/transformers/commit/aad13b87ed59f2afcfaebc985f403301887a35fc"><code>aad13b8</code></a>
v5.3.0</li>
<li><a
href="https://github.com/huggingface/transformers/commit/f6c63a61156fc0799a839f5de0219cad857c84a0"><code>f6c63a6</code></a>
protect imports (<a
href="https://redirect.github.com/huggingface/transformers/issues/44437">#44437</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/fd6bc380c8854a370fbc9f68a157895d84dce7d7"><code>fd6bc38</code></a>
[vllm + v5 fix] handle TokenizersBackend fallback properly for v5 (<a
href="https://redirect.github.com/huggingface/transformers/issues/44255">#44255</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/30c480166a95342fefdd9d727fc2a163bea7b2b1"><code>30c4801</code></a>
Fix CLI NameError: name 'TypeAdapter' is not defined (<a
href="https://redirect.github.com/huggingface/transformers/issues/44256">#44256</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/ee4c22078ff3987cbab669f332ff022d4fa89469"><code>ee4c220</code></a>
Enforce min length in some generate tests (<a
href="https://redirect.github.com/huggingface/transformers/issues/44401">#44401</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/a4f3df01aa9eab510768ea4396779b896b1ed8ab"><code>a4f3df0</code></a>
[tiny] Add olmo_hybrid to tokenizer auto-mapping (<a
href="https://redirect.github.com/huggingface/transformers/issues/44416">#44416</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/13135882276c0e4f72c921fc01a26f02e2137128"><code>1313588</code></a>
Update PR template (<a
href="https://redirect.github.com/huggingface/transformers/issues/44415">#44415</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/7235d44257e7e4765317d475622e2085a09c9e3b"><code>7235d44</code></a>
Add eurobert (<a
href="https://redirect.github.com/huggingface/transformers/issues/39455">#39455</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/f60c4e9423a2063fd0e313428ebbb3d5d1e6bdd6"><code>f60c4e9</code></a>
Add Qwen3.5 support for sequence classification (<a
href="https://redirect.github.com/huggingface/transformers/issues/44406">#44406</a>)</li>
<li><a
href="https://github.com/huggingface/transformers/commit/fa7f4b68df0c629f321821671b8988200a49e59d"><code>fa7f4b6</code></a>
update the expected output for qwen2_5_vl w/ pytorch 2.10 XPU (<a
href="https://redirect.github.com/huggingface/transformers/issues/44426">#44426</a>)</li>
<li>Additional commits viewable in <a
href="https://github.com/huggingface/transformers/compare/v5.0.0rc3...v5.3.0">compare
view</a></li>
</ul>
</details>
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Signed-off-by: dependabot[bot] <su...@github.com>
Co-authored-by: dependabot[bot] <49...@users.noreply.github.com>
Co-authored-by: Xinyuan Lin <xi...@uci.edu>
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---
amber/LICENSE-binary-python | 3 +--
amber/operator-requirements.txt | 2 +-
2 files changed, 2 insertions(+), 3 deletions(-)
diff --git a/amber/LICENSE-binary-python b/amber/LICENSE-binary-python
index 82ca22ba09..afd33d9547 100644
--- a/amber/LICENSE-binary-python
+++ b/amber/LICENSE-binary-python
@@ -233,7 +233,7 @@ Python packages:
- safetensors==0.8.0
- tenacity==8.5.0
- tokenizers==0.22.2
- - transformers==5.0.0rc3
+ - transformers==5.3.0
- tzdata==2026.2
- websocket-client==1.9.0
- yarl==1.24.2
@@ -283,7 +283,6 @@ Python packages:
- sqlalchemy==2.0.37
- strictyaml==1.7.3
- typer==0.25.1
- - typer-slim==0.24.0
- typing-inspection==0.4.2
- tzlocal==2.1
- urllib3==2.7.0
diff --git a/amber/operator-requirements.txt b/amber/operator-requirements.txt
index 3487fdbde5..99de2e11a3 100644
--- a/amber/operator-requirements.txt
+++ b/amber/operator-requirements.txt
@@ -27,5 +27,5 @@ torch==2.12.0+cpu ; platform_system == "Linux" and platform_machine == "x86_64"
torch==2.12.0 ; platform_system != "Linux" or platform_machine != "x86_64"
scikit-learn==1.5.0
-transformers==5.0.0rc3
+transformers==5.3.0
scikit-image==0.25.2