# Docs for v2 can be found by changing the above selector ^
from together import Together
import os
client = Together(
api_key=os.environ.get("TOGETHER_API_KEY"),
)
file = open("audio.wav", "rb")
response = client.audio.translations.create(
model="openai/whisper-large-v3",
file=file,
language="es",
)
print(response.text){
"text": "Hello, world!"
}Translates audio into English
# Docs for v2 can be found by changing the above selector ^
from together import Together
import os
client = Together(
api_key=os.environ.get("TOGETHER_API_KEY"),
)
file = open("audio.wav", "rb")
response = client.audio.translations.create(
model="openai/whisper-large-v3",
file=file,
language="es",
)
print(response.text){
"text": "Hello, world!"
}Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Audio file upload or public HTTP/HTTPS URL. Supported formats .wav, .mp3, .m4a, .webm, .flac.
Model to use for translation
openai/whisper-large-v3 Target output language. Optional ISO 639-1 language code. If omitted, language is set to English.
"en"
Optional text to bias decoding.
The format of the response
json, verbose_json Sampling temperature between 0.0 and 1.0
0 <= x <= 1Controls level of timestamp detail in verbose_json. Only used when response_format is verbose_json. Can be a single granularity or an array to get multiple levels.
segment, word ["word", "segment"]OK
The translated text
"Hello, world!"
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