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hyperonym / basaran

Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
MIT License
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build(deps): update transformers[sentencepiece] requirement from ~=4.27.4 to ~=4.28.0 #123

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Updates the requirements on transformers[sentencepiece] to permit the latest version.

Release notes

Sourced from transformers[sentencepiece]'s releases.

v4.28.0: LLaMa, Pix2Struct, MatCha, DePlot, MEGA, NLLB-MoE, GPTBigCode

LLaMA

The LLaMA model was proposed in LLaMA: Open and Efficient Foundation Language Models. It is a collection of foundation language models ranging from 7B to 65B parameters. You can request access to the weights here then use the conversion script to generate a checkpoint compatible with Hugging Face

Pix2Struct, MatCha, DePlot

Pix2Struct is a pretrained image-to-text model for purely visual language understanding, which can be finetuned on tasks containing visually-situated language. Pix2Struct has been fine-tuned on various tasks and datasets, ranging from image captioning and visual question answering (VQA) over different inputs (books, charts, science diagrams) to captioning UI components, and others.

Mega

MEGA proposes a new approach to self-attention with each encoder layer having a multi-headed exponential moving average in addition to a single head of standard dot-product attention, giving the attention mechanism stronger positional biases. This allows MEGA to perform competitively to Transformers on standard benchmarks including LRA while also having significantly fewer parameters. MEGA’s compute efficiency allows it to scale to very long sequences, making it an attractive option for long-document NLP tasks.

GPTBigCode

The model is a an optimized GPT2 model with support for Multi-Query Attention.

NLLB-MoE

The mixture of experts version of the NLLB release has been added to the library.

Serializing 8bit models

You can now push 8bit models and/or load 8bit models directly from the Hub, save memory and load your 8bit models faster! An example repo here

Breaking Changes

Ordering of height and width for the BLIP image processor

Notes from the PR:

The BLIP image processor incorrectly passed in the dimensions to resize in the order (width, height). This is reordered to be correct.

In most cases, this won't have an effect as the default height and width are the same. However, this is not backwards compatible for custom configurations with different height, width settings and direct calls to the resize method with different height, width values.

... (truncated)

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codecov-commenter commented 1 year ago

Codecov Report

Patch and project coverage have no change.

Comparison is base (04d865f) 94.23% compared to head (2e9cdfb) 94.23%.

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