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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 ~=4.28.1 to ~=4.29.0 #190

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.

v4.29.0: Transformers Agents, SAM, RWKV, FocalNet, OpenLLaMa

Transformers Agents

Transformers Agent is a new API that lets you use the library and Diffusers by prompting an agent (which is a large language model) in natural language. That agent will then output code using a set of predefined tools, leveraging the appropriate (and state-of-the-art) models for the task the user wants to perform. It is fully multimodal and extensible by the community. Learn more in the docs

SAM

SAM (Segment Anything Model) was proposed in Segment Anything by Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alex Berg, Wan-Yen Lo, Piotr Dollar, Ross Girshick.

The model can be used to predict segmentation masks of any object of interest given an input image.

RWKV

RWKV suggests a tweak in the traditional Transformer attention to make it linear. This way, the model can be used as recurrent network: passing inputs for timestamp 0 and timestamp 1 together is the same as passing inputs at timestamp 0, then inputs at timestamp 1 along with the state of timestamp 0 (see example below).

This can be more efficient than a regular Transformer and can deal with sentence of any length (even if the model uses a fixed context length for training).

FocalNet

The FocalNet model was proposed in Focal Modulation Networks by Jianwei Yang, Chunyuan Li, Xiyang Dai, Lu Yuan, Jianfeng Gao. FocalNets completely replace self-attention (used in models like ViT and Swin) by a focal modulation mechanism for modeling token interactions in vision. The authors claim that FocalNets outperform self-attention based models with similar computational costs on the tasks of image classification, object detection, and segmentation.

OpenLLaMa

The Open-Llama model was proposed in Open-Llama project by community developer s-JoL.

The model is mainly based on LLaMA with some modifications, incorporating memory-efficient attention from Xformers, stable embedding from Bloom, and shared input-output embedding from PLAM. And the model is pre-trained on both Chinese and English, which gives it better performance on Chinese language tasks.

Assisted Generation

Assisted generation is a new technique that lets you speed up generation with large language models by using a smaller model as assistant. The assistant model will be the ones doing multiple forward pass while the LLM will merely validate the tokens proposed by the assistant. This can lead to speed-ups up to 10x!

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codecov-commenter commented 1 year ago

Codecov Report

Patch and project coverage have no change.

Comparison is base (e0e0df6) 94.54% compared to head (33423ac) 94.54%.

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Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #190 +/- ## ======================================= Coverage 94.54% 94.54% ======================================= Files 7 7 Lines 330 330 ======================================= Hits 312 312 Misses 18 18 ```

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