Skip to main content

A sentiment analysis platform with AI runner and trainer components

Project description

Airosentris

Airosentris is a sentiment analysis platform that includes powerful components for training and running AI models. Designed for ease of use, it enables developers to integrate sentiment analysis capabilities into their applications quickly.

Features

  • AiroRunner: Execute trained sentiment analysis models efficiently.
  • AiroTrainer: Train sentiment analysis models using customizable algorithms.
  • Easy Integration: Seamlessly integrate with your existing applications.
  • Highly Customizable: Tailor the AI models to fit specific requirements.

Installation

You can install Airosentris via pip:

pip install airosentris

Installing PyTorch with CUDA 12.1 on Windows

Check CUDA Version

To determine the version of CUDA installed on your system, you can use the following command:

nvcc --version

This command checks the NVIDIA CUDA Compiler Driver version, which is part of the CUDA Toolkit. It will output the CUDA version currently installed.

Install PyTorch with GPU Support

To install PyTorch with GPU support for CUDA 12.1, follow these steps:

Step 1: Open Command Prompt

Open Command Prompt or your preferred terminal.

Step 2: Install PyTorch

Run the following command to install PyTorch with CUDA 12.1 support:

pip install torch==2.3.1+cu121 --extra-index-url https://download.pytorch.org/whl/cu121

This command installs the specified version of PyTorch (2.3.1) with CUDA 12.1 support. The --extra-index-url flag points to the PyTorch wheel (whl) files for CUDA 12.1.

Step 3: Verify the Installation

To verify that PyTorch is correctly installed and is using the GPU, run the following Python code:

import torch
print(torch.__version__)
print(torch.cuda.is_available())
print(torch.cuda.get_device_name(0))

This code will:

  • Print the PyTorch version.
  • Check if CUDA is available.
  • Print the name of the GPU device if available.

Example Output

You should see an output similar to this if everything is correctly set up:

2.3.1
True
NVIDIA GeForce GTX 1080

Additional Notes

  • Ensure that your CUDA drivers are properly installed and match the version you intend to use with PyTorch.
  • If you do not have CUDA installed, you can download and install the CUDA Toolkit from the NVIDIA CUDA website.
  • Make sure you have the appropriate version of cuDNN installed, which is typically bundled with the CUDA Toolkit.

By following these steps, you should be able to install and verify PyTorch with GPU support for CUDA 12.1 on your Windows system.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

airosentris-0.1.9.tar.gz (34.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

airosentris-0.1.9-py3-none-any.whl (46.5 kB view details)

Uploaded Python 3

File details

Details for the file airosentris-0.1.9.tar.gz.

File metadata

  • Download URL: airosentris-0.1.9.tar.gz
  • Upload date:
  • Size: 34.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.11

File hashes

Hashes for airosentris-0.1.9.tar.gz
Algorithm Hash digest
SHA256 d2631ff145aee01dbac11f6f6bb3348938670add664f448a4c1beb6ceface4cb
MD5 8914c3663e7f90fe2a83eb5d46526f46
BLAKE2b-256 36a5456242b07954e4904df0e53223605bf5c18c13b187e25e950138fcd6ee20

See more details on using hashes here.

File details

Details for the file airosentris-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: airosentris-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 46.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.11

File hashes

Hashes for airosentris-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 5c3022c05fd7733db9c0c9b397f0cc14f2d5493567874992762c84ab851e8d92
MD5 0b01f5279ffab0ec1e797d1b77999064
BLAKE2b-256 094d74f23c1505c5b6002faf555355a2226f7227410796b70f6e3d7383172798

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page