v0.12.0

Summary

Add PaliGemma, Llama 3, and Phi 3 models.

PaliGemma quickstart, see a complete usage on Kaggle.

pali_gemma_lm = keras_nlp.models.PaliGemmaCausalLM.from_preset(
    "pali_gemma_3b_224"
)
pali_gemma_lm.generate(
    inputs={
        "images": images,
        "prompts": prompts,
    }
)

What's Changed

• Add CodeGemma 1.1 presets by @grasskin in #1617
• Fix rope scaling factor by @abuelnasr0 in #1605
• Fix the issue of propagating training argument in subclasses by @james77777778 in #1623
• Pass kwargs to tokenizer when creating preprocessor by @SamanehSaadat in #1632
• Add phi3 by @abuelnasr0 in #1597
• Add LLaMA 3 tokenizer and preset by @tirthasheshpatel in #1584
• Export missing llama 3 symbol by @mattdangerw in #1633
• PaliGemma by @mattdangerw in #1636
• Update pali_gemma_presets.py by @divyashreepathihalli in #1637
• Update version to 0.13.0 for the master branch by @mattdangerw in #1640
• Update llama3 preset versions by @mattdangerw in #1641

Full Changelog: v0.11.1...v0.12.0

v0.11.1

Summary

• Add new Code Gemma 1.1 presets, which improve on Code Gemma performance.

What's Changed

• Add CodeGemma 1.1 presets by @grasskin in #1617
• Version bump 0.11.1.dev0 by @grasskin in #1618
• Version bump 0.11.1 by @grasskin in #1619

Full Changelog: v0.11.0...v0.11.1

v0.11.0

Summary

This release has no major feature updates, but changes the location our source code is help. Source code is split into a src/ and api/ directory with an explicit API surface similar to core Keras.

When adding or removing new API in a PR, use ./shell/api_gen.sh to update the autogenerated api/ files. See our contributing guide.

What's Changed

• Change the order of importing keras by @james77777778 in #1596
• Add backend info to HF model card by @SamanehSaadat in #1599
• Bump required kagglehub version to 0.2.4 by @SamanehSaadat in #1600
• Bump bert_tiny_en_uncased_sst2 classifier version by @SamanehSaadat in #1602
• Allow a task preprocessor to be an argument in from_preset by @SamanehSaadat in #1603
• API Generation by @sampathweb in #1608
• Update readme with some recent changes by @mattdangerw in #1575
• Bump the python group with 2 updates by @dependabot in #1611
• Version bump 0.11.0.dev0 by @mattdangerw in #1615
• Unexport models from the 0.11 release by @mattdangerw in #1614
• Version bump 0.11.0 by @mattdangerw in #1616

New Contributors

• @james77777778 made their first contribution in #1596

Full Changelog: v0.10.0...v0.11.0

v0.10.0

Summary

• Added support for Task (CausalLM and Classifier) saving and loading which allows uploading Tasks.
• Added basic Model Card for Hugging Face upload.
• Added support for a positions array in our RotaryEmbedding layer.

What's Changed

• 0.9 is out, nightly should be a preview of 0.10 now by @mattdangerw in #1570
• Do the reverse embedding in the same dtype as the input embedding by @mattdangerw in #1548
• Add support for positions array in keras_nlp.layers.RotaryEmbedding layer by @tirthasheshpatel in #1571
• Support Task Saving/Loading by @SamanehSaadat in #1547
• Improve error handling for non-keras model loading attempts by @SamanehSaadat in #1577
• Add Model Card for Hugging Face Upload by @SamanehSaadat in #1578
• Add Saving Tests by @SamanehSaadat in #1590
• Improve error handling for missing TensorFlow dependency in keras_nlp. by @SamanehSaadat in #1585
• Fix Keras import by @sampathweb in #1593
• Check kagglehub version before upload by @SamanehSaadat in #1594
• Version bump to 0.10.0.dev0 by @SamanehSaadat in #1595
• Version bump 0.10.0.dev1 by @SamanehSaadat in #1601
• Version bump to 0.10.0.dev2 by @SamanehSaadat in #1604
• Version bump to 0.10.0 by @SamanehSaadat in #1606

Full Changelog: v0.9.3...v0.10.0

v0.9.3

Patch release with fixes for Llama and Mistral saving.

What's Changed

• Fix saving bug for untied weights with keras 3.2 by @mattdangerw in #1568
• Version bump for dev release by @mattdangerw in #1569
• Version bump 0.9.3 by @mattdangerw in #1572

Full Changelog: v0.9.2...v0.9.3

v0.9.2

Summary

• Initial release of CodeGemma.
• Bump to a Gemma 1.1 version without download issues on Kaggle.

What's Changed

• Fix print_fn issue in task test by @SamanehSaadat in #1563
• Update presets for code gemma by @mattdangerw in #1564
• version bump 0.9.2.dev0 by @mattdangerw in #1565
• Version bump 0.9.2 by @mattdangerw in #1566

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

v0.9.1

Patch fix for bug with stop_token_ids.

What's Changed

• Fix the new stop_token_ids argument by @mattdangerw in #1558
• Fix tests with the "auto" default for stop token ids by @mattdangerw in #1559
• Version bump for 0.9.1 by @mattdangerw in #1560

Full Changelog: v0.9.0...v0.9.1

v0.9.0

The 0.9.0 release adds new models, hub integrations, and general usability improvements.

Summary

• Added the Gemma 1.1 release.
• Added the Llama 2, BLOOM and ELECTRA models.
• Expose new base classes. Allow from_preset() on base classes.
  • keras_nlp.models.Backbone
  • keras_nlp.models.Task
  • keras_nlp.models.Classifier
  • keras_nlp.models.CausalLM
  • keras_nlp.models.Seq2SeqLM
  • keras_nlp.models.MaskedLM
• Some initial features for uploading to model hubs.
  • backbone.save_to_preset, tokenizer.save_to_preset, keras_nlp.upload_preset.
  • from_preset and upload_preset now work with the Hugging Face Models Hub.
  • More features (task saving, lora saving), and full documentation coming soon.
• Numerical fixes for the Gemma model at mixed_bfloat16 precision. Thanks unsloth for catching!

# Llama 2. Needs Kaggle consent and login, see https://github.com/Kaggle/kagglehub
causal_lm = keras_nlp.models.LlamaCausalLM.from_preset(
    "llama2_7b_en",
    dtype="bfloat16", # Run at half precision for inference.
)
causal_lm.generate("Keras is a", max_length=128)
# Base class usage.
keras_nlp.models.Classifier.from_preset("bert_base_en", num_classes=2)
keras_nlp.models.Tokenizer.from_preset("gemma_2b_en")
keras_nlp.models.CausalLM.from_preset("gpt2_base_en", dtype="mixed_bfloat16")

What's Changed

• Add dtype arg to Gemma HF conversion script by @nkovela1 in #1452
• Fix gemma testing import by @mattdangerw in #1462
• Add docstring for PyTorch conversion script install instructions by @nkovela1 in #1471
• Add an annotation to tests that need kaggle auth by @mattdangerw in #1470
• Fix Mistral memory consumption with JAX and default dtype bug by @tirthasheshpatel in #1460
• Bump the master version to 0.9 by @mattdangerw in #1473
• Pin to TF 2.16 RC0 by @sampathweb in #1478
• Fix gemma rms_normalization's use of epsilon by @cpsauer in #1472
• Add FalconBackbone by @SamanehSaadat in #1475
• CI - Add kaggle creds to pull model by @sampathweb in #1459
• bug in example for ReversibleEmbedding by @TheCrazyT in #1484
• doc fix for constrastive sampler by @mattdangerw in #1488
• Remove broken link to masking and padding guide by @mattdangerw in #1487
• Fix a typo in causal_lm_preprocessors by @SamanehSaadat in #1489
• Fix dtype accessors of tasks/backbones by @mattdangerw in #1486
• Auto-labels 'gemma' on 'gemma' issues/PRs. by @shmishra99 in #1490
• Add BloomCausalLM by @abuelnasr0 in #1467
• Remove the bert jupyter conversion notebooks by @mattdangerw in #1492
• Add FalconTokenizer by @SamanehSaadat in #1485
• Add FalconPreprocessor by @SamanehSaadat in #1498
• Rename 176B presets & Add other presets into bloom_presets.py by @abuelnasr0 in #1496
• Add bloom presets by @abuelnasr0 in #1501
• Create workflow for auto assignment of issues and for stale issues by @sachinprasadhs in #1495
• Update requirements to TF 2.16 by @sampathweb in #1503
• Expose Task and Backbone by @mattdangerw in #1506
• Clean up and add our gemma conversion script by @mattdangerw in #1493
• Don't auto-update JAX GPU by @sampathweb in #1507
• Keep rope at float32 precision by @grasskin in #1497
• Bump the python group with 2 updates by @dependabot in #1509
• Fixes for the LLaMA backbone + add dropout by @tirthasheshpatel in #1499
• Add LlamaPreprocessor and LlamaCausalLMPreprocessor by @tirthasheshpatel in #1511
• Always run the rotary embedding layer in float32 by @tirthasheshpatel in #1508
• CI: Fix psutil - Remove install of Python 3.9 and alias of python3 by @sampathweb in #1514
• Update gemma_backbone.py for sharding config. by @qlzh727 in #1491
• Docs/modelling layers by @mykolaskrynnyk in #1502
• Standardize docstring by @sachinprasadhs in #1516
• Support tokenization of special tokens for word_piece_tokenizer by @abuelnasr0 in #1397
• Upload Model to Kaggle by @SamanehSaadat in #1512
• Add scoring mode to MistralCausalLM by @RyanMullins in #1521
• Add Mistral Instruct V0.2 preset by @tirthasheshpatel in #1520
• Add Tests for Kaggle Upload Validation by @SamanehSaadat in #1524
• Add presets for Electra and checkpoint conversion script by @pranavvp16 in #1384
• Allow saving / loading from Huggingface Hub preset by @Wauplin in #1510
• Stop on multiple end tokens by @grasskin in #1518
• Fix doc: mistral_base_en -> mistral_7b_en by @asmith26 in #1528
• Add lora example to GemmaCausalLM docstring by @SamanehSaadat in #1527
• Add LLaMA Causal LM with 7B presets by @tirthasheshpatel in #1526
• Add task base classes; support out of tree library extensions by @mattdangerw in #1517
• Doc fixes by @mattdangerw in #1530
• Run the LLaMA and Mistral RMS Layer Norm in float32 by @tirthasheshpatel in #1532
• Adds score API to GPT-2 by @RyanMullins in #1533
• increase pip timeout to 1000s to avoid connection resets by @sampathweb in #1535
• Adds the score API to LlamaCausalLM by @RyanMullins in #1534
• Implement compute_output_spec() for tokenizers with vocabulary. by @briango28 in #1523
• Remove staggler type annotiations by @mattdangerw in #1536
• Always run SiLU activation in float32 for LLaMA and Mistral by @tirthasheshpatel in #1540
• Bump the python group with 2 updates by @dependabot in #1538
• Disallow saving to preset from keras 2 by @SamanehSaadat in #1545
• Fix the rotary embedding computation in LLaMA by @tirthasheshpatel in #1544
• Fix re-compilation bugs by @mattdangerw in #1541
• Fix preprocessor from_preset bug by @mattdangerw in #1549
• Fix a strange issue with preprocessing layer output types by @mattdangerw in #1550
• Fix lowercase bug in wordpiece tokenizer by @abuelnasr0 in #1543
• Small docs updates by @mattdangerw in #1553
• Add a few new preset for gemma by @mattdangerw in #1556
• Remove the dev prefix for 0.9.0 release by @mattdangerw in #1557

New Contributors

• @cpsauer made their first contribution in #1472
• @SamanehSaadat made their first contribution in #1475
• @TheCrazyT made their first contribution in #1484
• @shmishra99 made their first contribution in #1490
• @sachinprasadhs made their first contribution in #1495
• @mykolaskrynnyk made their first contribution in #1502
• @RyanMullins made their first contribution in #1521
• @Wauplin made their first contribution in #1510
• @asmith26 made their first contribution in #1528
• @briango28 made their first contribution in #1523

Full Changelog: v0.8.2...v0.9.0

v0.8.2

Summary

• Mistral fixes for dtype and memory usage. #1458

What's Changed

• Fix Mistral memory consumption with JAX and default dtype bug by @tirthasheshpatel in #1460
• Version bump for dev release by @mattdangerw in #1474

Full Changelog: v0.8.1...v0.8.2.dev0

v0.8.1

Minor fixes to Kaggle Gemma assets.

What's Changed

• Update to the newest version of Gemma on Kaggle by @mattdangerw in #1454
• Dev release 0.8.1.dev0 by @mattdangerw in #1456
• 0.8.1 version bump by @mattdangerw in #1457

Full Changelog: v0.8.0...v0.8.1