v0.5.3

Fixed

• Loading generation config with nil attributes
• Generating with :no_repeat_ngram_length when using lower precision

v0.5.2

Fixed

• Fixed loading sharded parameters in the safetensors format

v0.5.1

Fixed

• Fixed loading Mistral configuration with attention window disabled

v0.5.0

This release changes the directory structure of the models cache, such that cached files from the same HuggingFace Hub repository are grouped in a separate subdirectory. This change is meant to simplify the process of manually removing specific models from the cache to free up space. As a result, the cache contents from prior versions are invalidated, so you most likely want to remove the current cache contents. To find the cache location run elixir -e 'Mix.install([{:bumblebee, "0.4.2"}]); IO.puts(Bumblebee.cache_dir())' (defaults to the standard cache location for the given operating system).

We also reduced memory usage during parameter loading (both when loading onto the CPU and GPU directly). Previously, larger models sometimes required loading parameters using CPU and only then transfering to the GPU, in order to avoid running out of GPU memory during parameter transformations. With this release this should no longer be the case. Loading parameters now has barely any memory footprint other than the parameters themselves.

Added

• Notebook on LLaMA 2 to the docs (#259)
• Mistral model (#264)
• Projection head models for ClipText and ClipVision (#276)
• Support more rotary embedding options for LLaMA required for Deepseek Coder (#285)
• Temperature generation option (#290)
• GPTBigCode model (used by Starcoder) (#294)
• Automatic detection of diffusers params files (specifying :params_filename for Stable Diffusion models is no longer necessary) (#301)
• :seed option to generation serving inputs (#303)
• :params_variant option to Bumblebee.load_model/2 for loading parameters of different precision (#309)
• :type option to Bumblebee.load_model/2 for loading model under a specific precision policy (#311)
• LCM scheduler (#320)
• Token summary to text generation output (#336)
• DINOv2 model (#334)
• :spec_overrides option to Bumblebee.load_model/2 (#340)
• Support for attention sliding window in Mistral (#341)

Changed

• (Breaking) Text generation to always return only the new text (for some models it used to include the prompt) (#302)
• Deprecated all options in Bumblebee.apply_tokenizer/3, these should now be set on the tokenizer using Bumblebee.configure/2 (#310)
• Reduced memory used when the :preallocate_params serving option is enabled (#317)
• (Breaking) Changed image size to maps in image featurizers (#329)
• (Breaking) Renamed ViT and DeiT :for_masked_image_modeling output from :logits to :pixel_values
• (Breaking) Renamed CLIP outputs :text_embeddings and :image_embeddings to singular
• (Breaking) Changed ResNet :pooled_state output to flatten the extra 1-sized axes
• Cache directory structure to group files by repository (#332)
• (Breaking) Changed the output of Bumblebee.Text.Generation.build_generate/4 to a map (#336)
• Reduced memory usage during parameter loading (#344)

Removed

• Removed the serving :seed option in favour of a runtime, per-input seed (#303)
• Conversational serving (#308)
• Specific tokenizer modules in favour of a single module (#310)
• Removed the deprecated Bumblebee.Audio.speech_to_text/5 (in favour of the more specific speech_to_text_whisper/5)

Fixed

• Featurizer batch template when image size is a tuple
• Error in concatenating results when running servings as partitioned (#282)
• Decoder cache being casted with low precision policies (#299)
• Loading of more recent VAE KL checkpoints (#305)
• Tokenizers truncation to account for trailing special tokens (#307)
• Loading models with auth token from within a HuggingFace Space (#314)
• Zero-shot classification serving to handle uppercased entailment token in model config (#327)
• Fixed text generation when using lower precision and encoder-decoder models (such as Whisper) (#346)

v0.4.2

Added

• More detailed error messages when loading fails (#256)

Changed

• Automatic detection there are no model parameters in the .bin format, but .safetensors is available (#256)

v0.4.1

Changed

• Aligned batch handling for serving run and batched run (#252)

Fixed

• Fixed :top_k upper bound in classification servings

v0.4.0

Added

• Chunking options to speech-to-text to support long audio transcription (#236)
• Support for Whisper timestamps and task/language configuration (#238)
• Support for streaming speech-to-text results (#242)
• Introduced featurizer batch phase that is compiled as part of the serving computation (#243)
• Removed possibly contentious Nx calls from serving postprocessing (#244, #245)

Changed

• Deprecated Bumblebee.Audio.speech_to_text/5 in favour of the more specific Bumblebee.Audio.speech_to_text_whisper/5
• Changed the tensors returned from embedding servings to use Nx.BinaryBackend

v0.3.1

Added

• LLaMA model (#199)
• GPT-NeoX model (#204)
• Option to customize scores function in classification tasks (#211)
• Text embedding serving (#214)
• Bumblebee.cache_dir/0 for discovering cache location (#220)
• Image embedding serving (#229)
• Support for compiling text servings for multiple sequence lengths (#228)
• Support for streaming chunks during text generation (#232)
• Added :preallocate_params option to all servings, useful with multiple GPUs (#233)
• Support for loading params in the .safetensors format (#231)

v0.3.0

In this release we moved all generation options to a new %Bumblebee.Text.GenerationConfig{} struct, which needs to be explicitly loaded and configured. A number of generation options is model-specific and they used to be a part of model specification, but encapsulating everything in a single struct improves the transparency of options origin and reconfiguration. The text generation servings (generation, speech-to-text and conversation) need to be adjusted as follows:

{:ok, model_info} = Bumblebee.load_model({:hf, "gpt2"})
{:ok, tokenizer} = Bumblebee.load_tokenizer({:hf, "gpt2"})
+{:ok, generation_config} = Bumblebee.load_generation_config({:hf, "gpt2"})

+generation_config = Bumblebee.configure(generation_config, max_new_tokens: 100)
+serving = Bumblebee.Text.generation(model_info, tokenizer, generation_config)
-serving = Bumblebee.Text.generation(model_info, tokenizer, max_new_tokens: 100)

Added

• Word-based aggregations for token classification (#174)
• BLIP model (#181)
• Text-to-image serving (#181)
• Generation option to avoid repeated n-grams (#182)
• Blenderbot model (#177)
• Option to load models from cache without outgoing traffic (#183)
• Whisper Phoenix demo (#184)
• Image channels normalization in featurizers (#189)
• T5 encoder model (#190)
• Contrastive search for sequence generation (#192)
• Multinomial sampling for sequence generation (#161)
• Support for loading sharded params checkpoints (#200)

Changed

• Model loading to not log params diff if everything is loaded correctly (#186)
• Moved all generation options to a new %Bumblebee.Text.GenerationConfig{} struct (#193)

v0.2.0

Added

• Support for Stable Diffusion v2 (#117)
• CamemBERT model (#110)
• XLM-RoBERTa model (#136)
• Support for configuring backend used by load_model (#140)
• Zero-shot classification serving (#121, #145)
• Support parameter files using Zip64 (#144)
• Notebook exemplifying fine-tuning with Axon (#102)
• Whisper model (#107)
• Speech-to-text serving (#107)
• Support for loading tokenizers with overridden special tokens (#141)
• Question answering serving (#157)
• T5 model (#159)
• Conversational serving (#165)
• DistilBERT model (#172)

Changed

• Cancel download request when the caller terminates (#135)
• Introduced explicit parameter mapping, which changed parameter names in all models (#148)

Fixed

• Initialization of parameters with mismatched shape