Stable Audio 3
Paper • 2605.17991 • Published • 12
AI & ML interests
This organization is maintained by the transformers team at Hugging Face and contains checkpoints of segmentation models such as SamHQ.
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nielsr
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paper to Daily Papers 5 days ago
nielsr
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nielsr
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papers to Daily Papers about 2 months ago
nielsr
submitted 3
papers to Daily Papers 2 months ago
Do VLMs Need Vision Transformers? Evaluating State Space Models as Vision Encoders
Paper • 2603.19209 • Published • 6
V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning
Paper • 2603.14482 • Published • 35
Omnilingual MT: Machine Translation for 1,600 Languages
Paper • 2603.16309 • Published • 23
nielsr
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nielsr
submitted 2
papers to Daily Papers 3 months ago
nielsr
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papers to Daily Papers 4 months ago
nielsr
submitted a
paper to Daily Papers 5 months ago
Post
3525
🚀 New blog: Maintain the unmaintainable – 1M+ Python LOC, 400+ models
How do you stop a million-line library built by thousands of contributors from collapsing under its own weight?
At 🤗 Transformers, we do it with explicit software-engineering tenets, principles that make the codebase hackable at scale.
🔍 Inside the post:
– One Model, One File: readability first — you can still open a modeling file and see the full logic, top to bottom.
– Modular Transformers: visible inheritance that cuts maintenance cost by ~15× while keeping models readable.
– Config-Driven Performance: FlashAttention, tensor parallelism, and attention scheduling are config-level features, not rewrites.
Written with @lysandre ,@pcuenq and @yonigozlan , this is a deep dive into how Transformers stays fast, open, and maintainable.
Read it here → transformers-community/Transformers-tenets
How do you stop a million-line library built by thousands of contributors from collapsing under its own weight?
At 🤗 Transformers, we do it with explicit software-engineering tenets, principles that make the codebase hackable at scale.
🔍 Inside the post:
– One Model, One File: readability first — you can still open a modeling file and see the full logic, top to bottom.
– Modular Transformers: visible inheritance that cuts maintenance cost by ~15× while keeping models readable.
– Config-Driven Performance: FlashAttention, tensor parallelism, and attention scheduling are config-level features, not rewrites.
Written with @lysandre ,@pcuenq and @yonigozlan , this is a deep dive into how Transformers stays fast, open, and maintainable.
Read it here → transformers-community/Transformers-tenets
nielsr
updated 3
models about 1 year ago
nielsr
updated a
collection about 1 year ago