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ML | Time Series

Conda env is built as, 12345678910micromamba env create -n MLmicromamba activate MLmicromamba install python==3.10micromamba install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvid
2025-01-13
ML
#AI #ML #pytorch

ML | stable-video-diffusion-img2vid-xt

stable-video-diffusion-img2vid-xt Stable Video Diffusion (SVD) Image-to-Video is a diffusion model that takes in a still image as a conditioning frame, and generates a video from it. Stable Video Diff
2025-01-10
ML
#AI #ML #pytorch #LLM #huggingface #stable-video-diffusion
ML | stable-diffusion

ML | stable-diffusion

stable-diffusion-xl-base-1.0 https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0 The stable-diffusion-xl-base-1.0 is a text-to-image generative model developed by Stability AI. Inputs
2025-01-09
ML
#AI #ML #pytorch #LLM #huggingface #stable-diffusion
ML | huggingface

ML | huggingface

Conda env 123456789# check CUDA Version:$ nvidia-smimicromamba env create -n huggingfacemicromamba activate huggingface micromamba install python==3.10micromamba install pytorch torchvision torchaudio
2025-01-08
ML
#AI #ML #pytorch #LLM #huggingface
ML | Scaling Law

ML | Scaling Law

Scaling Law In machine learning, a neural scaling law is an empirical scaling law that describes how neural network performance changes as key factors are scaled up or down. These factors typically in
2025-01-08
ML
#AI #ML #pytorch #LLM
ML | GPU Memory for ML model

ML | GPU Memory for ML model

GPU Memory you need to serve any ML models System Memory (RAM) is not ideal for this purpose because it is slower than GPU memory. GPU memory, also known as VRAM (Video Memory) or GDDR (Graphics DDR),
2025-01-07
ML
#AI #ML #pytorch #NVIDIA
CFD | Boussinesq approximation (buoyancy)

CFD | Boussinesq approximation (buoyancy)

Boussinesq approximation (buoyancy) In fluid dynamics, the Boussinesq approximation is used in the field of buoyancy-driven flow (also known as natural convection). It ignores density differences exce
2025-01-03
CFD
#HPC #OpenFOAM
ML | PINN | DeepXDE

ML | PINN | DeepXDE

DeepXDE DeepXDE 是一款开源且高度模块化的科学计算工具,以深度学习为核心,提供多种数据、物理机理及数理融合的模型,如PINN、DeepONet、MFNN等,同时支持多种类型微分方程,如常微分方程、偏微分方程的定义及求解,可有效解决复杂科学计算问题。 基于所提供的深度学习求解模型,DeepXDE具备以下典型的功能特点: 高度模块化:DeepXDE提供多种支持调用、组合的模块,如计算域
2025-01-03
ML
#PINN #AI #DeepONet #ML #DeepXDE

NWP | Bias Correction

應用「模式輸出統計」校正數碼氣溫預報 | HKO | 2011 多元線性回歸及卡爾曼濾波 出現次數最多的最佳因子,首三位為2米溫度、925hPa經向風及850hPa溫度 應用「模式輸出統計」校正相對濕度及風的數碼預報 | HKO | 2012 把2010年9月至2011年8月的數據分為四季,分別找出不同統計模型在四季及全年(即2010年9月至2011年8月)的最佳因子組合。 不同季節的比較
2025-01-02
NWP
#NWP #AI #ML
ML | CorrDiff (NVIDIA)

ML | CorrDiff (NVIDIA)

News 生成式AI與傳統數值天氣預報的結合NVIDIA CorrDiff天氣降尺度模型 | 科學月刊 | 2024-07-15 輝達(NVIDIA)執行長黃仁勳今(2024)年3月在美國舉辦的GTC(GPU technology conference)大會及6月在臺灣舉辦的臺北國際電腦展(COMPUTEX)上,皆展示了一項稱為「CorrDiff」( Corrector Diffusion )
2025-01-02
ML
#AI #ML #pytorch #Diffusion #UNet #NVIDIA
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