Python library for easily interacting with trained machine learning models
Project description
gradio_testfallback
Python library for easily interacting with trained machine learning models
Installation
pip install gradio_testfallback
Usage
import gradio as gr
from gradio_testfallback import TestFallback
with gr.Blocks() as demo:
gr.Markdown(
"# Change the value (keep it JSON) and the front-end will update automatically."
)
TestFallback(value={"message": "Hello from Gradio!"}, label="Static")
# if __name__ == "__main__":
print(demo)
demo.launch()
TestFallback
Initialization
name | type | default | description |
---|---|---|---|
value |
Any
|
None |
None |
label |
str | None
|
None |
None |
info |
str | None
|
None |
None |
show_label |
bool | None
|
None |
None |
container |
bool
|
True |
None |
scale |
int | None
|
None |
None |
min_width |
int | None
|
None |
None |
interactive |
bool | None
|
None |
None |
visible |
bool
|
True |
None |
elem_id |
str | None
|
None |
None |
elem_classes |
list[str] | str | None
|
None |
None |
render |
bool
|
True |
None |
load_fn |
Callable | None
|
None |
None |
every |
float | None
|
None |
None |
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
gradio_testfallback-0.0.2.tar.gz
(36.3 kB
view hashes)
Built Distribution
Close
Hashes for gradio_testfallback-0.0.2.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | ecdbfd3deeeb5855f715b39d01f6b547cc43e8b2890cad4609bed69ebf1c063e |
|
MD5 | 1bfd4c75d227e3ca3b9c6b13df48c526 |
|
BLAKE2b-256 | 25a729a54acfc40f43dfedb25f5d22a3a6df463801326f650c4fac8134c4df50 |
Close
Hashes for gradio_testfallback-0.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 86ccb3393fd968828d7050579118959645f3e9f85761c77d8fe2f3c1c77e04aa |
|
MD5 | 2781b9faff4d09a4fc1bc13f79931f3f |
|
BLAKE2b-256 | dd57b83046ff621c2d3c70a523565623471f46e183e1d8c4b1b058fbbffe9373 |