Send text to girlfriend in the morning

Last update: Oct 25, 2022

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Overview

Girlfriend Text

Send text to girlfriend (or really anyone with a phone number) in the morning

1. Configure your settings in `utils.py`.

phone_number = "phone number" # enter the target phone number inside quotation marks. use the format "+15555555555"
message = ["Good Morning Babe", "Good morning my love", "Good morning cutie"] # just make sure the message is inside quotation marks. An example is "Did you sleep well?"
scheduled_time = "08:00" # make sure the hour has 2 digits (24-hour standard).

Note: If you want to send a message everyday at 8:45 AM, you will need to set scheduled_time = "08:45" in utils.py

2. Install requirements: `pip install -r requirements.txt`

3. Run the script with: `python3 main.py`

Owner

Paras Adhikary

Entrepreneur, video creator, and software engineer.

GitHub Repository

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Send text to girlfriend in the morning

Related tags

Overview

Girlfriend Text

1. Configure your settings in `utils.py`.

2. Install requirements: `pip install -r requirements.txt`

3. Run the script with: `python3 main.py`

Owner

Paras Adhikary

Libtorch yolov3 deepsort

TuckER: Tensor Factorization for Knowledge Graph Completion

3rd Place Solution of the Traffic4Cast Core Challenge @ NeurIPS 2021

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Code for "LoRA: Low-Rank Adaptation of Large Language Models"

The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

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Official implementation of particle-based models (GNS and DPI-Net) on the Physion dataset.

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[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

Send text to girlfriend in the morning

Related tags

Overview

Girlfriend Text

1. Configure your settings in utils.py.

2. Install requirements: pip install -r requirements.txt

3. Run the script with: python3 main.py

Owner

Paras Adhikary

Libtorch yolov3 deepsort

TuckER: Tensor Factorization for Knowledge Graph Completion

3rd Place Solution of the Traffic4Cast Core Challenge @ NeurIPS 2021

Tensorflow Tutorials using Jupyter Notebook

Perform zero-order Hankel Transform for an 1D array (float or real valued).

Code for "LoRA: Low-Rank Adaptation of Large Language Models"

The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation".

Official implementation of particle-based models (GNS and DPI-Net) on the Physion dataset.

Codes for TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization.

A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading

Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions

PyGCL: A PyTorch Library for Graph Contrastive Learning

The CLRS Algorithmic Reasoning Benchmark

Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".

Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Sky Computing: Accelerating Geo-distributed Computing in Federated Learning

A Tensorfflow implementation of Attend, Infer, Repeat

[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

1. Configure your settings in `utils.py`.

2. Install requirements: `pip install -r requirements.txt`

3. Run the script with: `python3 main.py`