miniforge
Pytorch
miniforge | Pytorch | |
---|---|---|
56 | 339 | |
5,306 | 78,016 | |
3.4% | 1.4% | |
7.7 | 10.0 | |
5 days ago | 2 days ago | |
Shell | Python | |
GNU General Public License v3.0 or later | BSD 1-Clause License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
miniforge
- Python 3.12
- Installing Anaconda on ChromeOS using Linux
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What is the difference between chat, cai-chat, and instruct, and how to use them?
Nope they don't use venv for any of the oobabooga# variants nor is it recommended for the git version. I'm using https://github.com/conda-forge/miniforge#mambaforge-pypy3 (better version of the recommended conda) for the git variant. The oobabooga* variant uses micro/miniconda (I suck with names) which you can easily drop into with cmd_?something? and does it all internally. Like whoever built that whole environment setup for the _windows/linux/mac did a great job.
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Build llama.cpp on Jetson Nano 2GB
wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-aarch64.sh .
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PSA: conda-libmamba-solver can cut two hours off of your Anaconda install, but has only 47 GitHub stars. It deserves more praise.
Mambaforge!
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A quick guide to using mamba-forge for python virtual environment management
Just to further clarify: you don't need mamba to avoid the Anaconda distribution. The place you get mambaforge also supplies (and originally supplied) miniforge, which is miniconda with conda-forge set as the default channel. All the *forge installers do in this regard is automatically set conda-forge as the default (and only) channel, which is something one can do manually with miniconda.
- Recommendations for Data Science Workflow
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path issue - cannot import modules in jupyter installed via pip3 (m1 mac)
I'd recommend using miniforge if you're comfortable with CLIs, otherwise https://www.anaconda.com/.
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How to get the best Conda environment experience in Codespaces
Tip 1: To use less of your Codespaces resources start with a smaller image like Miniconda or Miniforge and install only what you need.
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Ask HN: Programs that saved you 100 hours? (2022 edition)
miniforge, no need to deal with conda environments anymore. https://github.com/conda-forge/miniforge
Pytorch
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AI enthusiasm #9 - A multilingual chatbotđŁđ¸
torch is a package to manage tensors and dynamic neural networks in python (GitHub)
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Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
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Library for Machine learning and quantum computing
TensorFlow
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call âprimalâ, is associated with a âdirectionâ tensor, which we call âtangentâ, the resultant new tensor object is called a âdual tensorâ for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
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Building a GPT Model from the Ground Up!
import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this
What are some alternatives?
mamba - The Fast Cross-Platform Package Manager
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
pyenv - Simple Python version management
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Poetry - Python packaging and dependency management made easy
flax - Flax is a neural network library for JAX that is designed for flexibility.
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
tinygrad - You like pytorch? You like micrograd? You love tinygrad! â¤ď¸ [Moved to: https://github.com/tinygrad/tinygrad]
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more