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Widget Examples

Note that each widget example can also optionally describe the corresponding model output, directly in the output property. See the spec for more details.

Natural Language Processing

Fill-Mask

widget:
- text: "Paris is the <mask> of France."
  example_title: "Capital"
- text: "The goal of life is <mask>."
  example_title: "Philosophy"

Question Answering

widget:
- text: "What's my name?"
  context: "My name is Clara and I live in Berkeley."
  example_title: "Name"
- text: "Where do I live?"
  context: "My name is Sarah and I live in London"
  example_title: "Location"

Summarization

widget:
- text: "The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930. It was the first structure to reach a height of 300 metres. Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft). Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct."
  example_title: "Eiffel Tower"
- text: "Laika, a dog that was the first living creature to be launched into Earth orbit, on board the Soviet artificial satellite Sputnik 2, on November 3, 1957. It was always understood that Laika would not survive the mission, but her actual fate was misrepresented for decades. Laika was a small (13 pounds [6 kg]), even-tempered, mixed-breed dog about two years of age. She was one of a number of stray dogs that were taken into the Soviet spaceflight program after being rescued from the streets. Only female dogs were used because they were considered to be anatomically better suited than males for close confinement."
  example_title: "First in Space"

Table Question Answering

widget:
- text: "How many stars does the transformers repository have?"
  table:
    Repository:
      - "Transformers"
      - "Datasets"
      - "Tokenizers"
    Stars:
      - 36542
      - 4512
      - 3934
    Contributors:
      - 651
      - 77
      - 34
    Programming language:
      - "Python"
      - "Python"
      - "Rust, Python and NodeJS"
  example_title: "Github stars"

Text Classification

widget:
- text: "I love football so much"
  example_title: "Positive"
- text: "I don't really like this type of food"
  example_title: "Negative"

Text Generation

widget:
- text: "My name is Julien and I like to"
  example_title: "Julien"
- text: "My name is Merve and my favorite"
  example_title: "Merve"

Text2Text Generation

widget:
- text: "My name is Julien and I like to"
  example_title: "Julien"
- text: "My name is Merve and my favorite"
  example_title: "Merve"

Token Classification

widget:
- text: "My name is Sylvain and I live in Paris"
  example_title: "Parisian"
- text: "My name is Sarah and I live in London"
  example_title: "Londoner"

Translation

widget:
- text: "My name is Sylvain and I live in Paris"
  example_title: "Parisian"
- text: "My name is Sarah and I live in London"
  example_title: "Londoner"

Zero-Shot Classification

widget:
- text: "I have a problem with my car that needs to be resolved asap!!"
  candidate_labels: "urgent, not urgent, phone, tablet, computer"
  multi_class: true
  example_title: "Car problem"
- text: "Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app."
  candidate_labels: "mobile, website, billing, account access"
  multi_class: false
  example_title: "Phone issue"

Sentence Similarity

widget:
- source_sentence: "That is a happy person"
  sentences:
    - "That is a happy dog"
    - "That is a very happy person"
    - "Today is a sunny day"
  example_title: "Happy"

Conversational

widget:
- text: "Hey my name is Julien! How are you?"
  example_title: "Julien"
- text: "Hey my name is Clara! How are you?"
  example_title: "Clara"

Feature Extraction

widget:
- text: "My name is Sylvain and I live in Paris"
  example_title: "Parisian"
- text: "My name is Sarah and I live in London"
  example_title: "Londoner"

Audio

Text-to-Speech

widget:
- text: "My name is Sylvain and I live in Paris"
  example_title: "Parisian"
- text: "My name is Sarah and I live in London"
  example_title: "Londoner"

Automatic Speech Recognition

widget:
- src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
  example_title: Librispeech sample 1
- src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
  example_title: Librispeech sample 2

Audio-to-Audio

widget:
- src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
  example_title: Librispeech sample 1
- src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
  example_title: Librispeech sample 2

Audio Classification

widget:
- src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
  example_title: Librispeech sample 1
- src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
  example_title: Librispeech sample 2

Voice Activity Detection

widget:
- src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
  example_title: Librispeech sample 1
- src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
  example_title: Librispeech sample 2

Computer Vision

Image Classification

widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
  example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
  example_title: Teapot

Object Detection

widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
  example_title: Football Match
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/airport.jpg
  example_title: Airport

Image Segmentation

widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
  example_title: Football Match
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/airport.jpg
  example_title: Airport

Image-to-Image

widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/canny-edge.jpg
  prompt: Girl with Pearl Earring # `prompt` field is optional in case the underlying model supports text guidance

Text-to-Image

widget:
- text: "A cat playing with a ball"
  example_title: "Cat"
- text: "A dog jumping over a fence"
  example_title: "Dog"

Document Question Answering

widget:
- text: "What is the invoice number?"
  src: "https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png"
- text: "What is the purchase amount?"
  src: "https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/contract.jpeg"

Visual Question Answering

widget:
- text: "What animal is it?"
  src: "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg"
- text: "Where is it?"
  src: "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg"

Zero-Shot Image Classification

widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-dog-music.png
  candidate_labels: playing music, playing sports
  example_title: Cat & Dog

Other

Structured Data Classification

widget:
- structured_data:
    fixed_acidity:
      - 7.4
      - 7.8
      - 10.3
    volatile_acidity:
      - 0.7
      - 0.88
      - 0.32
    citric_acid:
      - 0
      - 0
      - 0.45
    residual_sugar:
      - 1.9
      - 2.6
      - 6.4
    chlorides:
      - 0.076
      - 0.098
      - 0.073
    free_sulfur_dioxide:
      - 11
      - 25
      - 5
    total_sulfur_dioxide:
      - 34
      - 67
      - 13
    density:
      - 0.9978
      - 0.9968
      - 0.9976
    pH:
      - 3.51
      - 3.2
      - 3.23
    sulphates:
      - 0.56
      - 0.68
      - 0.82
    alcohol:
      - 9.4
      - 9.8
      - 12.6
  example_title: "Wine"

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