🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
This week focused on reliability fixes across multiple fronts. MoE models now properly return router logits from all layers that compute them, OLLaVA and Qwen3-VL received corrections for multi-image and multi-axis position handling, and quantized and per-layer cache support was improved. The team…
Get this in your inbox every Monday →A deterministic 0–100 hygiene score — README, license, CI, tests, docs, and freshness.
Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in transformers's README, structure, and recent commits — answers won't invent code they haven't seen.
A Monday email with what shipped, in plain English — no account needed.
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[tests] Skip onnx.exactness for BitForImageClassification (ORT fp32 drift) (#49366)
Link the padding side section from SSM and hybrid model docs (#49247)
Revert "[CI] Temporarily disable AMD scheduled CI trigger" (#49271) (#49362)
fix(cohere_compass): add video to input_modalities (#49320) (#49323)
GPT-OSS: read the clamped SwiGLU's alpha and limit from the config (#49346)
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 30 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.
