compiler-aware-nas-sr

(★ 26)

[ECCV2022] Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution

Owner Repos

FMEDiffusion ★ 17

[NeurIPS2024] Fast and Memory-Efficient Video Diffusion Using Streamlined Inference

Python
ToR_SSM ★ 11

[EMNLP2024] Rethinking Token Reduction for State Space Models

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OmniMem ★ 9

Official Implementation for OmniMem: Scalable and Adaptive Memory Retrieval for Long Video Generation

Python

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  • .gitignore
  • export_onnx.py
  • loss_config.py
  • prepare_dataset.py
  • pretrain.py
  • pretraining.bash
  • README.md
  • search.bash
  • search.py

# Use via CDN

jsDelivr

jsDelivr serves any public GitHub repository as a CDN with zero setup. Pick a version and a file to get a ready-to-paste link and snippet.

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Example

Command Glossary

Commands referenced in this DOCs, explained below.

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conda activate

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Activate a conda environment.
See also: `conda deactivate`.

conda activate myenv

Activate an existing environment named `myenv`:

conda activate {{path/to/myenv}}

Activate an existing environment located at custom path:

conda activate --stack myenv

Stack `myenv` environment on top of a previous environment making libraries/commands/variables from both accessible:

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conda create

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Create new conda environments.

conda create {{[-y|--yes]}} {{[-n|--name]}} py39 python=3.9 "numpy>=1.11" scipy

Create a new environment named `py39`, install Python 3.9, NumPy v1.11 or above in it, and the latest stable version of SciPy. Say yes to all confirmations:

conda create {{[-n|--name]}} myenv --file {{file1.yml}} --file {{file2.yml}}

Create a new environment named `myenv` and install packages listed in files:

conda create {{[-p|--prefix]}} {{path/to/myenv}}

Create a new environment at a custom path (i.e. prefix):

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conda install

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Install packages into an existing conda environment.

conda install {{package1 package2 ...}}

Install one or more package into the currently active conda environment:

conda install {{[-c|--channel]}} conda-forge {{package}}

Install a single package into the currently active conda environment using channel conda-forge:

conda install {{[-c|--channel]}} conda-forge --override-channels {{package}}

Install a single package into the currently active conda environment using channel conda-forge and ignoring other channels:

// repository documentation