Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts
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Updated
Aug 7, 2024 - Python
Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
This adapter reads exported TOTP secrets and stores those by calling the interface of a target authenticator that is running on your personal computer.
This is the official repository of the papers "Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers" and "Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of Adapters".
[ACMMM'24] MoBA: Mixture of Bi-directional Adapter for Multi-modal Sarcasm Detection
Round-trip serialization/deserialization of any Python object to/from any serialization format including Avro and JSON.
A generalized framework for subspace tuning methods in parameter efficient fine-tuning.
Comparing popular Parameter Efficient Fine-Tuning (PEFT) techniques for Large Language Models
Convert any graph-like data structures to mermaid code and vice versa.
Client implementation for the Debug Adapter Protocol (https://microsoft.github.io/debug-adapter-protocol) that is used in IDEs, editors and other tools to communicate with different debuggers
Structure-aware adapter fine-tuning PLMs, with high training speed and impressive performance.
VLSM-Adapter: Finetuning Vision-Language Segmentation Efficiently with Lightweight Blocks
[CVPR 2024] Memory-based Adapters for Online 3D Scene Perception
Adapting Segment Anything Model for Medical Image Segmentation
Convert a Raspberry Pi into a HID relay that translates Bluetooth keyboard and mouse input to USB. Minimal configuration. Zero hassle.
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