Repo: https://
github.com/pytorch-labs/g
pt-fast
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@sumanth_077
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PyTorch Labs GPT-Fast Repository Link Shared
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PyTorch Releases GPT-Fast for Efficient Text Generation
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Pytorch released GPT-fast!⚡️
— Sumanth (@Sumanth_077) 5 mars 2024
This is a simple and efficient implementation of pytorch-native transformer text generation:
Here are some key features:
– Very low latency
– <1000 lines of python
– No dependencies other than PyTorch and sentencepiece
– int8/int4 quantization
-… pic.twitter.com/chk4ms5nf6Pytorch released GPT-fast! This is a simple and efficient implementation of pytorch-native transformer text generation: Here are some key features: – Very low latency
– <1000 lines of python
– No dependencies other than PyTorch and sentencepiece
– int8/int4 quantization
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Python ML MLOps CV NLP LLMs Daily Tutorials
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If you are interested in: – Python – Machine Learning – MLOps – CV/NLP – LLMs Find me → @Sumanth_077 Everyday, I share tutorials on above topics! Like/RT the first tweet to help this reach more people!
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Predict Method: Binary Classification with 0.5 Threshold
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Finally the predict method: It uses the trained model to make predictions based on input features. This method applies a threshold of 0.5 to make binary predictions, returning 1 for positive class predictions and 0 for negative class predictions.
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Define the Fit Method for Model Training with Gradient Descent
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Define the "fit" method that does the training of model The method takes input data "X" and the corresponding target values "y" It also updates the weights and bias using gradient descent.
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Compute Cost Function: Cross-Entropy Loss for Classification
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Compute Cost Function Next define the cost function, which is the cross-entropy loss, used to measure the error between predicted probabilities and actual labels.
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Sigmoid Activation Function: Computing Class Probability in Machine Learning
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Define Sigmoid Activation Function: This is used to compute the probability of the target class. Sigmoid function takes a linear combination of input features and returns values between 0 and 1, which represent the probability that a given sample belongs to the positive class.
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LogisticRegression Class Implementation with Five Essential Methods
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Define LogisticRegression class to encapsulate the functionality of Logistic Regression The class has 5 methods: __init__, sigmoid, compute_cost, fit and predict. First let's Initialize learning rate, epochs, weights and bias attributes using the __init__ method.
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Logistic Regression Implementation Guide from Scratch
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Logistic Regression clearly explained and implemented from scratch in Python:
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Microsoft Launches Free 18-Lesson Generative AI Course on GitHub
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Microsoft launched the best course on Generative AI! The free 18 lesson course is available on Github and will teach you everything you need to know to start building Generative AI applications.