pytorch-apple-silicon
docker-python
pytorch-apple-silicon | docker-python | |
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3 | 5 | |
387 | 2,350 | |
- | 0.9% | |
3.0 | 9.0 | |
11 months ago | 9 days ago | |
Jupyter Notebook | Python | |
MIT License | Apache License 2.0 |
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pytorch-apple-silicon
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Help ‼️
Hi, The picture is all of my virtural environment. Before today, I usually command conda activate arm64_tf can enter my virtural environment. But today I want to find the pytorch running in GPU and then step-by-step this github https://github.com/mrdbourke/pytorch-apple-silicon. After this process, my conda activate arm64_tf is didn't work. Becomes I need to enter the file cd /Users/calvin/opt/anaconda3/envs and then conda activate ./arm64_tf. I don't know why become complicated.
- FLaNK Stack Weekly 27 March 2023
- Docker set up machine learning with PyTorch on M1 recs?
docker-python
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Docker set up machine learning with PyTorch on M1 recs?
If that works you can then reuse Kaggle docker for example https://github.com/Kaggle/docker-python
- Has anyone here set up a Kaggle Docker container?
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How do you load the Kaggle theme for JupyterLab?
I like the Kaggle theme for Jupyter Lab better than the stock one. I know you can download Kaggle's whole open source environment and run your own server via docker, but I just want the theme for my own env.
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File Directory not found problems happening again randomly, read_csv confusion
# This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python # For example, here's several helpful packages to load import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) # Input data files are available in the read-only "../input/" directory # For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory import os for dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename)) # You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All" # You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session
- Ask HN: API to run Python code, what can go wrong?
What are some alternatives?
spring-boot-startup-report - Spring Boot Startup Report library generates an interactive Spring Boot application startup report that lets you understand what contributes to the application startup time and perhaps helps to optimize it.
learntools - Tools and tests used in Kaggle Learn exercises
wiremock-spring-boot - WireMock Spring Boot drastically simplifies testing HTTP clients in Spring Boot & Junit 5 based integration tests.
Orphic - A natural language shell interface for *nix systems
FateZero - [ICCV 2023 Oral] "FateZero: Fusing Attentions for Zero-shot Text-based Video Editing"
cursor - The AI-powered code editor
aquarium - AI-controlled Linux Containers
ml-ane-transformers - Reference implementation of the Transformer architecture optimized for Apple Neural Engine (ANE)
lakehouse-sharing - A Table format agnostic data sharing framework