To run this customT5 need a training dataset which have two coloumns "UseCase" which is a target and "Sentences" which is a source variable.
Ex: !pip install T5Custom
from T5Custom import main
import pandas as pd
path = "https://github.com/nikuraj006/customeT5/blob/main/T5_training%20Data.csv"
df = pd.read_csv(path).dropna()
main.trainModel(df,True) # to train Model
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Release files for T5Custom 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| T5Custom-1.1.0.tar.gz | 21.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| T5Custom-1.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:45.3 kB
Release files / T5Custom-1.1.0.tar.gz
| Download URL | T5Custom-1.1.0.tar.gz |
|---|---|
| Size | 21.2 kB |
| Tags | Source |
|
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| Uploaded via |
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Release files / T5Custom-1.1.0-py3-none-any.whl
| Download URL | T5Custom-1.1.0-py3-none-any.whl |
|---|---|
| Size | 24.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/4.0.2 CPython/3.9.6
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