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Releases: ludwig-ai/ludwig

Ludwig v0.10.4

30 Jul 00:11
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What's Changed

  • Small typo in dequantization script by @arnavgarg1 in #3993
  • Docs: update visualize.py by @eltociear in #4001
  • [MAINTENANCE] Most Recent Version of matplotlib breaks ptitprince and seaborn method calls. by @alexsherstinsky in #4007
  • [MAINTENANCE] Make the implementation for the fix of the ViTEncoder to ensure that the transformers.ViTModel returns the output_attentions more elegant (and cuts on the amount of code) by @alexsherstinsky in #4008
  • Fix mnist source by @mhabedank in #4011
  • Support for freezing pretrained vision model layers with regex by @ethanreidel in #3981
  • Add Phi-3 Support by @arnavgarg1 in #4014

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Full Changelog: v0.10.3...v0.10.4

Ludwig v0.10.3

08 Apr 23:13
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Full Changelog: v0.10.2...v0.10.3

Release v0.10.2

21 Mar 20:24
30fe47b
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What's New

  • Add support for RSLoRA and DoRA by @arnavgarg1 in #3948
    To enable, set the corresponding flag to true in config (can be used in conjunction):
    adapter:
        type:  lora
        use_rslora:  false
        use_dora: false
  • Add support for eval batch size tuning for LLMs on local backend by @arnavgarg1 in #3957
    To enable, set "eval_batch_size" to "auto" in the trainer section:
    trainer:
        eval_batch_size:  auto
  • Enable loading model weights from training checkpoint by @geoffreyangus in #3969
    To enable, pass from_checkpoint=True to LudwigModel.load():
LudwigModel.load(model_dir, from_checkpoint=True)

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Full Changelog: v0.10.1...v0.10.2

Ludwig v0.10.1

28 Feb 07:30
b46e615
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  • Fixed a critical bug in Gemma model fine-tuning that prevented the model from learning when to stop generation. This is accomplished by using eos token in target tensor for instruction-tuning by @geoffreyangus in #3945

Full Changelog: v0.10.0...v0.10.1

v0.10.0

22 Feb 19:20
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Full Changelog: v0.9.3...v0.10.0

v0.9.3

23 Jan 04:10
45fcd27
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Full Changelog: v0.9.2...v0.9.3

v0.9.2: Fixes for OOM and other errors in Ludwig 0.9.1

16 Jan 21:14
10b8bb0
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What's Changed

  • fix: Handle missing and unexpected keys during LLMEncoder state dict load by @jeffkinnison in #3841
  • fix: Add name and description classmethods to IA3Config by @jeffkinnison in #3844
  • Improve IA3 long description by @arnavgarg1 in #3845
  • fix: Handle missing and unexpected keys during LLMEncoder state dict load, part 2 by @jeffkinnison in #3843
  • Update description for max_new_tokens to explain the dynamic setting behavior in our docs by @arnavgarg1 in #3847
  • Add default LoRA target modules for Mixtral and Mixtral instruct by @arnavgarg1 in #3852
  • QOL: Fail config validation if a user tries to use ECD with a text output feature and an LLM encoder. by @justinxzhao in #3792
  • Pin minimum transformers to 4.36 for Mixtral and Phi support by @arnavgarg1 in #3854
  • Revert hack that leads to OOM during fine-tuning by @arnavgarg1 in #3858
  • Add support for exporting models to Carton by @VivekPanyam in #3797
  • [Maintenance] Bump minimum tokenizers to 0.15 by @arnavgarg1 in #3856
  • fix: correct typo in FeatureCollection by @dennisrall in #3863
  • Convert test main script in algorithm_utils to unit test by @dennisrall in #3864
  • Allow hyperopt config to be loaded from a file by @arnavgarg1 in #3865
  • fix: unify ludwig training set metadata and hf pad token by @geoffreyangus in #3860
  • Add a utility to detect LLM usage in a config by @jeffkinnison in #3869
  • Early stop training if model weights have nan or inf tensors by @arnavgarg1 in #3740
  • Scrub credentials from model_hyperparameters.json and description.json by @Infernaught in #3866
  • [Maintenance] Bump minimum torch version to 2.0.0 by @arnavgarg1 in #3873
  • [Maintenance] Fix docker images by pinning ray==2.3.1, daft==0.1.20, unpinning proto, and using torch 2.1.1. by @justinxzhao in #3872
  • [BUGFIX] Guard against UnicodeEncodeError when saving validation results in Google Colab environment by @alexsherstinsky in #3875
  • Docker image fixes part 2: pin to torch==2.1.0, add dependency for urllib<2 by @arnavgarg1 in #3877
  • Add custom prepare_for_trianing logic to ECD model for LLM encoder adapter initialization by @jeffkinnison in #3874
  • qol: Fix some lints. by @justinxzhao in #3868
  • [Maintenance] Docker Image Fix part 3: fix torchaudio 2.1.0 dependencies by installing libsox-dev and update API by @arnavgarg1 in #3879
  • Add streaming support for zero shot inference by @arnavgarg1 in #3878
  • [Maintenance] Remove torchdata pin for nightly install by @arnavgarg1 in #3855
  • Add per-step token utilization to tensorboard and progress tracker. by @justinxzhao in #3867
  • Set use_reentrant to False for gradient checkpointing by @arnavgarg1 in #3882
  • [BUGFIX] Pinning torch nightly to January 13, 2024 to avoid AttributeError by @alexsherstinsky in #3885

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Full Changelog: v0.9.1...v0.9.2

v0.9.1

20 Dec 21:47
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Full Changelog: v0.9...v0.9.1

v0.9: Mixtral, Phi, Zephyr, and text classification for LLMs

19 Dec 22:20
4e848db
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v0.8.6

13 Oct 15:47
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What's Changed

  • Add consumer complaints generation dataset by @connor-mccorm in #3685
  • Set the metadata only during first training run by @Infernaught in #3684
  • Add ability to upload Ludwig models to Predibase. by @martindavis in #3687
  • Log additional per-GPU information in model metadata files and GPU utilization on tensorboard. by @justinxzhao in #3712
  • QoL: Only log generation config being used once at inference time by @arnavgarg1 in #3715
  • [MAINTENANCE] Adding typehint annotations in backend and data components and fixing mypy errors. by @alexsherstinsky in #3709
  • QoL: Limit top-level trainer logging messages such as saving model or resuming model training to main coordinator process by @arnavgarg1 in #3718
  • Add sample_size as a global preprocessing parameter by @Infernaught in #3650
  • QOL: Update recommended vscode settings. by @justinxzhao in #3717
  • Add new fine-tuning notebooks to README by @arnavgarg1 in #3722
  • Dynamically set max_new_tokens based on output feature length, GMSL and model window size by @arnavgarg1 in #3713
  • Fix issue while logging cuda device utilization to tensorboard by @arnavgarg1 in #3727

Full Changelog: v0.8.5...v0.8.6