datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
workflow-curatedcustom-component-gallery-backupsgradio-dependents
Dataset Card for "gradio-dependents"
More Information needed
docsNYC-Airbnb-Open-Datagradio-reviewsgradio-pi-sessions
Pi Sessions
Redacted Pi coding-agent session traces.
Files use the raw session JSONL layout compatible with julien-c/synthtraces:
sessions/<project>/<timestamp>_<session-id>.jsonl
Each line is one Pi session event (session, model_change, message, tool_result, etc.).
Gradio-Docs
Gradio Docs
These markdown docs were taken from https://github.com/gradio-app/gradio/tree/main/guides
I just wanted to have a copy in the Hub 🤗
mcp-server-bench-gradio-optimized
🔬 Gradio vs FastMCP Benchmark Report
Generated: 2026-03-02T13:04:10.857215
Total scenarios: 48
Executive Summary
echo: Fastmcp wins (96.6 vs 176.5 RPS, 1.83x difference)
Gradio best config: concurrency_limit=nan
fibonacci: Fastmcp wins (43.5 vs 57.1 RPS, 1.31x difference)
Gradio best config: concurrency_limit=nan
async_sleep: Gradio wins (93.1 vs 80.2 RPS, 1.16x difference)
Gradio best config: concurrency_limit=nan
payload_echo: Fastmcp wins (82.5 vs 164.8 RPS… See the full description on the dataset page: https://huggingface.co/datasets/kshitijthakkar/mcp-server-bench-gradio-optimized.gradio-agents-mcp-hackathon-certificates
Dataset Card for "gradio-agents-mcp-hackathon-certificates"
More Information needed
openjev-cpu-gradio-kit
⚖️ OpenJev on CPU — a zero-GPU decision API Space
Runs the official openjev/openjev-GGUF
OpenJev-Q4_K_M.gguf (16.5 GB, ~4.8 bits, text-only) with
llama-cpp-python on CPU only
(n_gpu_layers=0) and serves the exact same /v1/systemone decision protocol as the
hosted openjev-server.
One forward pass per question — no generation, no chain-of-thought.
Same prompt layout, same temperature (T=0.85), same noul calibration (noul_t=1.829074), same confidence formulas.
Choice / score /… See the full description on the dataset page: https://huggingface.co/datasets/broadfield/openjev-cpu-gradio-kit.theme-gallery
Gradio Theme Gallery
Community-contributed themes for Gradio. This dataset powers the theme gallery at gradio.app/themes.
How to add a theme
Add an entry to manifest.json with your theme's metadata:
{
"id": "your-username/your-theme",
"name": "Your Theme Name",
"author": "your-username",
"description": "A short description of your theme.",
"hf_space_id": "your-username/your-theme-space",
"colors": {
"primary": "#hex",
"secondary": "#hex"… See the full description on the dataset page: https://huggingface.co/datasets/gradio/theme-gallery.mcp-server-bench-gradio
🔬 Gradio vs FastMCP Benchmark Report
Generated: 2026-03-04T10:26:47.242725
Total scenarios: 12
Executive Summary
echo: Gradio wins (151.4 vs 126.2 RPS, 1.2x difference)
Gradio best config: concurrency_limit=1.0
async_sleep: Gradio wins (126.6 vs 43.9 RPS, 2.88x difference)
Gradio best config: concurrency_limit=1.0
Throughput (Requests/Second)
('fastmcp', 'mcp_streamable')
('gradio', 'mcp_streamable')
('async_sleep', 1)
17.54
16.57… See the full description on the dataset page: https://huggingface.co/datasets/kshitijthakkar/mcp-server-bench-gradio.gradio-workflow-eval-arena
gr.Workflow Eval Arena — sample rows
Five rows, one per scorer branch, for the gr.Workflow eval arena example.
column
meaning
id
stable row identifier
task_type
exact, numeric, json, free-form, truncation
prompt
the prompt sent to every candidate
gold
reference answer
meta
free-text note
Deliberately tiny: it exists to exercise every scoring path, not to rank models. Any conclusion about model quality drawn from five rows is not statistically meaningful.
mcp-server-bench-gradio-optimized-full-bench
🔬 Gradio vs FastMCP Benchmark Report
Generated: 2026-03-02T21:04:48.460108
Total scenarios: 337
Executive Summary
echo: Fastmcp wins (100.9 vs 189.9 RPS, 1.88x difference)
Gradio best config: concurrency_limit=1.0
fibonacci: Fastmcp wins (45.5 vs 55.0 RPS, 1.21x difference)
Gradio best config: concurrency_limit=nan
json_transform: Fastmcp wins (94.5 vs 165.4 RPS, 1.75x difference)
Gradio best config: concurrency_limit=5.0
async_sleep: Fastmcp wins (94.0 vs 104.3… See the full description on the dataset page: https://huggingface.co/datasets/kshitijthakkar/mcp-server-bench-gradio-optimized-full-bench.comprehensive-gradio-coding-datasetgradio_files_oldnew_saving_json
Dataset Card for Dataset Name
Dataset Summary
[More Information Needed]
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data… See the full description on the dataset page: https://huggingface.co/datasets/gradio/new_saving_json.gradio-backticks
Dataset Card for "gradio-backticks"
More Information needed
chatinterface_with_image_csv
Dataset Card for Dataset Name
Dataset Summary
[More Information Needed]
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data… See the full description on the dataset page: https://huggingface.co/datasets/gradio/chatinterface_with_image_csv.gradio-reasoningSamples in this benchmark were generated by RELAI using the following data source(s):
Data Source Name: gradio
Documentation Data Source Link: https://www.gradio.app/docs
Data Source License: https://github.com/gradio-app/gradio/blob/main/LICENSE
Data Source Authors: Observable AI Benchmarks by Data Agents © 2025 RELAI.AI. Licensed under CC BY 4.0. Source: https://relai.ai
edition_2237_gradio-custom-component-gallery-backups-readymade
edition_2237_gradio-custom-component-gallery-backups-readymade
A Readymade by TheFactoryX
Original Dataset
gradio/custom-component-gallery-backups
Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as art.
What we did:
Selected the original dataset from Hugging Face
Shuffled each column independently
Destroyed all row-wise relationships
Preserved structure, removed meaning
The… See the full description on the dataset page: https://huggingface.co/datasets/TheFactoryX/edition_2237_gradio-custom-component-gallery-backups-readymade.workflow-curated-v2edition_1519_gradio-custom-component-gallery-backups-readymade
edition_1519_gradio-custom-component-gallery-backups-readymade
A Readymade by TheFactoryX
Original Dataset
gradio/custom-component-gallery-backups
Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as art.
What we did:
Selected the original dataset from Hugging Face
Shuffled each column independently
Destroyed all row-wise relationships
Preserved structure, removed meaning
The… See the full description on the dataset page: https://huggingface.co/datasets/TheFactoryX/edition_1519_gradio-custom-component-gallery-backups-readymade.edition_1572_gradio-custom-component-gallery-backups-readymade
edition_1572_gradio-custom-component-gallery-backups-readymade
A Readymade by TheFactoryX
Original Dataset
gradio/custom-component-gallery-backups
Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as art.
What we did:
Selected the original dataset from Hugging Face
Shuffled each column independently
Destroyed all row-wise relationships
Preserved structure, removed meaning
The… See the full description on the dataset page: https://huggingface.co/datasets/TheFactoryX/edition_1572_gradio-custom-component-gallery-backups-readymade.edition_1615_gradio-custom-component-gallery-backups-readymade
edition_1615_gradio-custom-component-gallery-backups-readymade
A Readymade by TheFactoryX
Original Dataset
gradio/custom-component-gallery-backups
Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as art.
What we did:
Selected the original dataset from Hugging Face
Shuffled each column independently
Destroyed all row-wise relationships
Preserved structure, removed meaning
The… See the full description on the dataset page: https://huggingface.co/datasets/TheFactoryX/edition_1615_gradio-custom-component-gallery-backups-readymade.gradio_docs_alpacaA dataset created from the gradio documentation page. The 2 main groups are components and guides, where components are have all the information about What they do, and their parameters.
This is a first attempt at generating a dataset for alpaca training, feedback is welcome, and improvements on this will be made
edition_2092_gradio-custom-component-gallery-backups-readymade
edition_2092_gradio-custom-component-gallery-backups-readymade
A Readymade by TheFactoryX
Original Dataset
gradio/custom-component-gallery-backups
Process
This dataset is a "readymade" - inspired by Marcel Duchamp's concept of taking everyday objects and recontextualizing them as art.
What we did:
Selected the original dataset from Hugging Face
Shuffled each column independently
Destroyed all row-wise relationships
Preserved structure, removed meaning
The… See the full description on the dataset page: https://huggingface.co/datasets/TheFactoryX/edition_2092_gradio-custom-component-gallery-backups-readymade.job-outputsgradioTest