Donut LLM Tools
Donut LLM Tools is a suite of two programs that helps you create dataset from wikipedia data and your own LLM with the created or already existing dataset.
Latest Version 24.05.29
How to install, import and use DonutLLM?
Installation
-
Before installing Donut LLM Tools, make sure you have Python
3.9or later till Python3.11. Note : Python3.12is not supported by PyTorch, hence Donut LLM Tools will also have trouble running in it. -
The dependencies for installing Donut LLM Tools are:
- DonutLLMCore (
pip install DonutLLMCore) - torch (Required by DonutLLMCore)
- torchvision (Required by CreateLLM, PyTorch)
- torchaudio (Required by CreateLLM, PyTorch)
- Wikipedia
Note : You need to check PyTorch website to find more about installation on devices with only CPU or with GPU. Donut LLM Tools support CPU, however it is very slow to train a model in CPU.
- DonutLLMCore (
-
After ensuring the installation of the above mentioned dependencies, do
pip install donut-llm-tools. -
You have now installed Donut LLM Tools in your device.
Importing and Using
from donutllmtools import Tools
Tools.DatasetCreator() # For creating wikipedia based datasets.
Tools.LLMCreator() # For creating/loading AI model from the above created dataset or a custom dataset.
The above code snippet is used to create a dataset and also train/load an AI model
from donutllmtools import HelpAndInfo
HelpAndInfo.help() # To view help.
HelpAndInfo.about() # To view details of the program.
HelpAndInfo.create_llm() # Also create LLM from HelpAndInfo class.
HelpAndInfo.create_dataset() # ALso create dataset from HelpAndInfo class.
HelpAndInfo.main() # To get a menu based interface for dataset creation or model load/creation.
The above code uses HelpAndInfo class which has the same functions from Tools class as well as help functions.
Metadata
Release files for Donut-LLM-Tools 24.5.29
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| donut_llm_tools-24.5.29.tar.gz | 4.6 kB | Without provenance | Details for donut_llm_tools-24.5.29.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| Donut_LLM_Tools-24.5.29-py3-none-any.whl | Python 3 | none | any | Details for Donut_LLM_Tools-24.5.29-py3-none-any.whl |
Total release size: 9.4 kB
Release files / donut_llm_tools-24.5.29.tar.gz
| Download URL | donut_llm_tools-24.5.29.tar.gz |
|---|---|
| Size | 4.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
1592ab1fda2a43d7624e778a7a2147a33c838e3e24f6507d47f71f9034866e9b
|
|
BLAKE2b-256 checksum How to use checksums |
8440516d17c52aeb8f7c059e91021427b4e2a78ba8549bc463f8457a126877b1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.0 CPython/3.11.9
|
Release files / Donut_LLM_Tools-24.5.29-py3-none-any.whl
| Download URL | Donut_LLM_Tools-24.5.29-py3-none-any.whl |
|---|---|
| Size | 4.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b82bfc49c94928cc6463ea3f77f384261e8993f3b44ccc591803dcac3d132130
|
|
BLAKE2b-256 checksum How to use checksums |
d1fac32b3a6690940e1827e2a300466c379851ad733c295b3081c70063371f82
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.0 CPython/3.11.9
|
Security for Donut-LLM-Tools 24.5.29
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.