type: collective_task
dataset_splits: ['train', 'dev']
tasks:
- name: zero_shot_translation
pipeline_labels: [pypeline@tensorflow]
task_labels: [translate]
inputs:
- type: text
format: json
prompt: Free-form text, no formatting restrictions
expected_input_types: ["text"]
examples: {"en": "Hello world", "de": "Hallo Welt"}
outputs:
- type: text
format: json
prompt: Free-form text, no formatting restrictions
expected_output_types: ["text"]
examples: {"en": "I am a large language model.", "de": "Ich bin ein grosses Sprachmodell."}
pipeline_params: {}
- name: text_to_speech
pipeline_labels: [pypeline@transformerxlsp]
task_labels: [tts]
inputs:
- type: text
format: json
prompt: Markdown, HTML, Unicode, or LaTeX, but avoid complex math notation
example: title="Hello World!"<\\title><::post.body=\\\nThis \\sout{is} an *italicized* text post.*```bash
{...<}`````.rst
metadata: {'tags': ''|None}
expected_input_types: ["text"]
examples: {EN: {""}, DE: {"#OpenSource #Synthesizer
// Einige Werte kann ich noch nicht liefern da keine Implementierung vorliegt."}}}, {"...
:{tag: 'jazz'}"/>}}`)}
outputs:
- type: audio
format: wav, opus, m4a
bitrate: 64kbps+
channel_count: 1
sample_rate: 22kHz+
rate: monophonic
pitch_range: 0.5-4 octaves
speed_range: +/- 5%
vibrato_depth: maximum of 3 semitones
dynamics_range: ppp-fff
silence_padding: >=8ms
prompt: Melodies, up to two verses per submission, please separate with commas. Monophony encouraged, unless improvisational techniques warrant chord progressions. Examples in EN, DE, ES, FR: {"en": "[0.7, 1, Eb4], 'Mary had a little lamb',[0.9, 1, Ab3,'Twinkle twinkle