llama-classification | Text classification with Foundation Language Model LLaMA

by sh0416 Python Version: v1.1.1 License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | llama-classification Summary

llama-classification is a Python library. llama-classification has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Text classification with Foundation Language Model LLaMA

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llama-classification has a low active ecosystem.

It has 3 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

llama-classification has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of llama-classification is v1.1.1

Quality

llama-classification has no bugs reported.

Security

llama-classification has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

llama-classification is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

llama-classification releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

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llama-classification Key Features

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llama-classification Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install llama-classification

Get the checkpoint from official LLaMA repository from here. 1-1. I assume that the checkpoint would be located in the project root direction and the contents would be arranged as follow. Prepare your python environment. I recommend using anaconda to segregate your local machine CUDA version.
Get the checkpoint from official LLaMA repository from here. 1-1. I assume that the checkpoint would be located in the project root direction and the contents would be arranged as follow. checkpoints ├── llama │ ├── 7B │ │ ├── checklist.chk │ │ ├── consolidated.00.pth │ │ └── params.json │ └── tokenizer.model
Prepare your python environment. I recommend using anaconda to segregate your local machine CUDA version. conda create -y -n llama-classification python=3.8 conda activate llama-classification conda install cudatoolkit=11.7 -y -c nvidia conda list cudatoolkit # to check what cuda version is installed (11.7) pip install -r requirements.txt

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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