v0.5.2

[0.5.2] - 2025-08-30

Changed

• Apply small input performance fix to goMLX backend

[0.5.1] - 2025-08-29

Changed

• Fix performance regression for small inputs

[0.5.0] - 2025-08-29

🚀 Generative pipeline in hugot!

• The new TextGenerationPipeline allows you to run generative models such as Gemma and Phi in golang. Kudos to Riley Oh for getting this one
  over the line!
• Currently only implemented for the ORT backend. Implementations for XLA and GO backend coming soon!
• See the documentation for how to get started

🚀 New pipelines: cross encoder and image classification

• The CrossEncoderPipeline implements the equivalent of sentence transformers' Cross Encoder. Kudos to
  Fábio Correia for providing the initial implementation
• The ImageClassificationPipeline implements the equivalent of Hugging Face's Image Classification pipeline

✨ Training improvements

• The training session to fine-tune embeddings now accept TrainEval and Eval datasets to compute in-sample and test statistics
• The training session now implements early stopping based on the loss on the Eval dataset. Early stopping is evaluated at the end of each training epoch.
• The training session now accepts a layer freezing configuration to specify which layers of the transformer will be frozen during fine-tuning

📝 Tokenization

• The go tokenizer now supports unigram tokenization

Changed

• Updated go to 1.25.0
• Upgraded GoMLX to 0.22.1

v0.5.1

[0.5.1] - 2025-08-29

Changed

• Fix performance regression for small inputs

[0.5.0] - 2025-08-29

🚀 Generative pipeline in hugot!

• The new TextGenerationPipeline allows you to run generative models such as Gemma and Phi in golang. Kudos to Riley Oh for getting this one
  over the line!
• Currently only implemented for the ORT backend. Implementations for XLA and GO backend coming soon!
• See the documentation for how to get started

🚀 New pipelines: cross encoder and image classification

• The CrossEncoderPipeline implements the equivalent of sentence transformers' Cross Encoder. Kudos to
  Fábio Correia for providing the initial implementation
• The ImageClassificationPipeline implements the equivalent of Hugging Face's Image Classification pipeline

✨ Training improvements

• The training session to fine-tune embeddings now accept TrainEval and Eval datasets to compute in-sample and test statistics
• The training session now implements early stopping based on the loss on the Eval dataset. Early stopping is evaluated at the end of each training epoch.
• The training session now accepts a layer freezing configuration to specify which layers of the transformer will be frozen during fine-tuning

📝 Tokenization

• The go tokenizer now supports unigram tokenization

Changed

• Updated go to 1.25.0
• Upgraded GoMLX to 0.22.1

v0.5.0

[0.5.0] - 2025-08-29

🚀 Generative pipeline in hugot!

• The new TextGenerationPipeline allows you to run generative models such as Gemma and Phi in golang. Kudos to Riley Oh for getting this one
  over the line!
• Currently only implemented for the ORT backend. Implementations for XLA and GO backend coming soon!
• See the documentation for how to get started

🚀 New pipelines: cross encoder and image classification

• The CrossEncoderPipeline implements the equivalent of sentence transformers' Cross Encoder. Kudos to
  Fábio Correia for providing the initial implementation
• The ImageClassificationPipeline implements the equivalent of Hugging Face's Image Classification pipeline

✨ Training improvements

• The training session to fine-tune embeddings now accept TrainEval and Eval datasets to compute in-sample and test statistics
• The training session now implements early stopping based on the loss on the Eval dataset. Early stopping is evaluated at the end of each training epoch.
• The training session now accepts a layer freezing configuration to specify which layers of the transformer will be frozen during fine-tuning

📝 Tokenization

• The go tokenizer now supports unigram tokenization

Changed

• Updated go to 1.25.0
• Upgraded GoMLX to 0.22.1

v0.4.3

What's Changed

• Upgraded to latest Rust and Go tokenizers
• Generalised output tensor types, added int64 support (preparation for text generation pipeline)
• Dependency updates and go 1.24.5

v0.4.2

What's Changed

• Tokenizers obey max_position_embeddings, closing issue #73
• Provided default ORT path in darwin/mac
• Dependency updates and go 1.24.4

v0.4.1

[0.4.1] - 2025-06-03

🚀 New Features

✨ Pure Go Backend

• Run inference and fine-tuning, all from native Go!
• Added NewGoSession() backend, enabling Hugot to run in pure Go environments without C dependencies
• Implements our most requested community feature using SimpleGo from GoMLX
• Optimized for simpler workloads and environments where cgo is restricted
• Works best with smaller models like all-MiniLM-L6-v2
• Performance sweet spot: batches of approximately 32 inputs per call

📊 Performance Notes

• The Go backend currently performs 5-20x slower than C backends
• For performance-critical applications, we recommend using C backends (XLA or ORT)
• Significant speed improvements expected with the introduction of SIMD in Go 1.25

🐞 Known Limitations

• The Go backend and tokenizer currently lack support for certain operators
• If you encounter compatibility issues, please open an issue
• As a temporary workaround, use a C backend until the issue is resolved

🚨 Breaking Changes

• Build Tag Requirements Updated:
  • For NewORTSession(): Add -tags "ORT" or -tags "ALL" to your build arguments
  • For NewXLASession(): Add -tags "XLA" or -tags "ALL" to your build arguments

Added

• SimpleGo backend and SugarMe tokenizers for running Hugot without C dependencies

Changed

• Upgraded CUDA libraries to 12.9
• Upgraded GoMLX for performance improvements and bugfixes.

v0.3.8

Full Changelog: v0.3.7...v0.3.8

v0.3.7

Full Changelog: v0.3.6...v0.3.7

v0.3.6

Full Changelog: v0.3.5...v0.3.6

v0.3.5

Full Changelog: v0.3.4...v0.3.5