Who contributed to Hugging Face on June 11, 2026?

7 developers shipped this update, including ArthurZucker, remi-or, xin3he, zucchini-nlp, sayakpaul, Wauplin, and hanouticelina.

What were the notable Hugging Face updates?

Release v5.11.0, Add deepseek 3.2 exp, and [CB] [Minor] Add data-parallel to overall script.

@huggingface

Transformers, Datasets, and the open AI-model layer

github ↗

Pick a date

Topics: Python AI / ML Full archive →

The Wire · Showcase

TRANSFORMERS V5.11 SHIPS WITH DIFFUSIONGEMMA, DEEPSEEK 3.2 QUANTIZATION LANDS

By RepoJournal · Filed 06:04 UTC on June 11, 2026 · About Hugging Face

7 people shipped this

ArthurZucker @ArthurZucker 1 cited

remi-or @remi-or 1 cited

xin3he @xin3he 1 cited

zucchini-nlp @zucchini-nlp 1 cited

sayakpaul @sayakpaul 1 cited

Wauplin @Wauplin 1 cited

hanouticelina @hanouticelina 1 cited

Transformers v5.11.0 arrives with a major new model addition and three critical inference wins that ship faster token generation and better GPU utilization.

The headline win is DiffusionGemma [1], an encoder-decoder architecture engineered to crush the sequential bottlenecks of standard causal models by using multi-canvas sampling during inference, shipping token generation that doesn't play the one-token-at-a-time game. Paired with that is DeepSeek V3.2 quantization support [2], which adds fine-grained FP8 quantization with module-level exclusion, letting you ship 4-bit weight inference without gutting model quality. The throughput story gets better: continuous batching benchmarks now support data parallelism [3], meaning an 8-GPU node doesn't bottleneck 16 benchmarks to a single GPU anymore. On the diffusers side, AutoRound quantization integration [4] brings W4A16 weight-only quantization, another efficiency play for deployment. Hub auth just went keyless [8] with OIDC token exchange through Trusted Publishers, eliminating the need to store HF_TOKEN secrets in CI. The test infrastructure tightened up across the board: transformers fixed multi-image span offsets [5] that vLLM needed to bump, diffusers refactored UNet tests to a modular pattern [6], and huggingface_hub added explicit xet/no_xet markers [7] to stop guessing which tests actually run.

Action items

→ Update to transformers v5.11.0 to get DiffusionGemma and DeepSeek quantization support if you're deploying inference huggingface/transformers [plan]
→ Integrate AutoRound quantization in diffusers if W4A16 deployment efficiency matters in your pipeline huggingface/diffusers [plan]
→ Adopt OIDC token exchange in CI workflows to remove stored HF_TOKEN secrets huggingface/huggingface_hub [plan]
→ Verify continuous batching benchmarks are tuned with data parallelism on multi-GPU nodes huggingface/transformers [monitor]

References

[1] Release v5.11.0 ↗ huggingface/transformers
[2] Add deepseek 3.2 exp ↗ huggingface/transformers
[3] [CB] [Minor] Add data-parallel to overall script ↗ huggingface/transformers
[4] Integrate AutoRound into Diffusers ↗ huggingface/diffusers
[5] Fix the offsets in processing ↗ huggingface/transformers
[6] [tests] refactor UNet model tests to align with the new pattern ↗ huggingface/diffusers
[7] [Tests] Add xet/no_xet pytest markers to filter Xet vs non-Xet tests ↗ huggingface/huggingface_hub
[8] [Auth] Keyless CI/CD auth via OIDC token exchange ↗ huggingface/huggingface_hub

Quick answers

What shipped in Hugging Face on June 11, 2026?: Transformers v5.11.0 arrives with a major new model addition and three critical inference wins that ship faster token generation and better GPU utilization. In total, 26 commits, 26 pull requests, and 2 releases landed.
Who contributed to Hugging Face on June 11, 2026?: 7 developers shipped this update, including ArthurZucker, remi-or, xin3he, zucchini-nlp, sayakpaul, Wauplin, and hanouticelina.
What were the notable Hugging Face updates?: Release v5.11.0, Add deepseek 3.2 exp, and [CB] [Minor] Add data-parallel to overall script.

TRANSFORMERS-CI SHIPS INTELLIGENT TEST TRIAGE, CUTS LLM NOISE 100X

Hugging Face's serge verify loop now distills 100KB failure tracebacks down to the actual assertion, runs every test 5 times to catch flakiness, and dispatches each failure category with a custom instruction before spinning GPU or consuming a single LLM token.

python 45 shipped 2-min read

@huggingface 2 days ago

TRL CI BURNS, BITSANDBYTES PINNED BELOW 0.50.0

Hugging Face's TRL training library is firefighting two separate CI failures overnight, forcing temporary pins on bitsandbytes and xfailing critical tests against a broken transformers dev build.

python 7 shipped 1-min read

@huggingface 3 days ago

TRANSFORMERS OVERHAULS LINEAR ATTENTION WHILE DEPRECATING LEGACY RESPONSE SCHEMA

The transformers library is retiring its fragile response_schema prototype in favor of streaming-compatible parsing, while simultaneously refactoring every linear attention model to use standardized convolution patterns.

python 70 shipped 2-min read

@huggingface 4 days ago

TRANSFORMERS SHIPS FSDP DISTRIBUTED TRAINING STACK, HUB LIBRARY PLUGS REDOS HOLE

Hugging Face landed distributed training orchestration in transformers while plugging a regex vulnerability that could stall untrusted card parsing for minutes.

+10

python 61 shipped 1-min read

Elsewhere on the wire

AI Agents about 21 hours ago

CLINE SHIPS FIVE CRITICAL AGENT FIXES AFTER END-TO-END TESTING BLITZ

Saoudrizwan just landed a cascade of fixes that prevent the agent loop from running wild, stop file reads from resolving to the wrong directory, and plug the compaction pipeline.

ai-agents 16 shipped 2-min read

Local LLMs about 21 hours ago

LLAMA.CPP SHIPS MINIMAX-M3 SPARSE ATTENTION, VLLM UNLOCKS HETEROGENEOUS PREFILL-DECODE

The inference stack gets a new model architecture and a fundamental shift in how prefill and decode can run on different hardware configurations.

+10

llms 125 shipped 1-min read

@CachyOS about 21 hours ago

GLIBC 2.43 REBUILD SHIPS, INSTALLER JUMPS TO C++26

CachyOS pushed glibc 2.43 through the pipeline while the CLI installer upgraded its C++ standard to C++26, signaling a major refresh across core infrastructure.

infra 97 shipped 1-min read

Elixir & Phoenix about 21 hours ago

ECTO FIXES SUBQUERY PLANNING IN JOINS, ELIXIR PATCHES IEX PARSING

Ecto's query planner now handles subqueries correctly in interpolated join filters, while Elixir fixes a syntax error that broke 'not in' as a continuation operator in IEx.