spokestack-python
Pytorch
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spokestack-python | Pytorch | |
---|---|---|
7 | 336 | |
132 | 77,783 | |
- | 2.4% | |
3.3 | 10.0 | |
over 2 years ago | 3 days ago | |
Python | Python | |
Apache License 2.0 | 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.
spokestack-python
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We're making it super easy to use voice in Python, and we want your feedback!
Our AutoML service will let you [redacted because we're not ready to say it publicly yet], using your own voice. Combining [redacted] with existing open-source SDK libraries & tutorials for [Python](https://github.com/spokestack/spokestack-python) allows you to utilize cutting-edge personalized voice technology.
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Sunday Daily Thread: What's everyone working on this week?
I’ve been working on this project for a while now. I’m really interested to discover if other developers want to add voice to their python projects.
I’ll be working on integrating spokestack into home-assistant
- Spokestack: Python Library for Voice Applications
- Spokestack: Embedded Voice Library for Python
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I love home assistant and I work on TTS in my day job. Should I do an add-on or an integration?
Ok so that’s my main concern. It seems like for distribution an integration is the way to go. Library is this for better context.
- Python Embedded Voice Library
Pytorch
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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 “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” 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
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Element-wise vs Matrix vs Dot multiplication
In PyTorch with * or mul(). ` or mul()` can multiply 0D or more D tensors by element-wise multiplication:
What are some alternatives?
picovoice - On-device voice assistant platform powered by deep learning
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Porcupine - On-device wake word detection powered by deep learning
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Caffe2
flax - Flax is a neural network library for JAX that is designed for flexibility.
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
neptune-client - 📘 The MLOps stack component for experiment tracking
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