content.raw: 📢 If you're looking for translating massive dataset of JSON-lines / CSV data with various set of source fields, then the following update would be relevant. So far and experimenting with adapting language specific Sentiment Analysis model, got a change to reforge and relaese bulk-translate 0.25.2.
content.type: text
content.value: 📢 If you're looking for translating massive dataset of JSON-lines / CSV data with various set of source fields, then the following update would be relevant. So far and experimenting with adapting language specific Sentiment Analysis model, got a change to reforge and relaese bulk-translate 0.25.2.
content.type: new_line
content.raw: ⭐️ 
content.type: text
content.value: ⭐️ 
content.href: https://github.com/nicolay-r/bulk-translate/releases/tag/0.25.2
content.raw: https://github.com/nicolay-r/bulk-translate/releases/tag/0.25.2
content.type: link
content.type: new_line
content.type: new_line
content.raw: The update has the following major features
content.type: text
content.value: The update has the following major features
content.type: new_line
content.raw: - Supporting schemas: all the columns to be translated are now could be declared within the same prompt-style format. using json this automatically allows to map them onto output fields
content.type: text
content.value: - Supporting schemas: all the columns to be translated are now could be declared within the same prompt-style format. using json this automatically allows to map them onto output fields
content.type: new_line
content.raw: - The related updates for shell execution mode: schema parameter is now available alongside with just a prompt usage before.
content.type: text
content.value: - The related updates for shell execution mode: schema parameter is now available alongside with just a prompt usage before.
content.type: new_line
content.type: new_line
content.raw: Benefit is that your output is invariant. You can extend and stack various translators with separated shell laucnhes.
content.type: text
content.value: Benefit is that your output is invariant. You can extend and stack various translators with separated shell laucnhes.
content.type: new_line
content.type: new_line
content.raw: Screenshot below is the application of the google-translate engine in manual batching mode.
content.type: text
content.value: Screenshot below is the application of the google-translate engine in manual batching mode.
content.type: new_line
content.raw: 🚀 Performance: 2.5 it / sec (in the case of a single field translation)
content.type: text
content.value: 🚀 Performance: 2.5 it / sec (in the case of a single field translation)
content.type: new_line
content.type: new_line
content.raw: 🌟 about bulk-translate: 
content.type: text
content.value: 🌟 about bulk-translate: 
content.href: https://github.com/nicolay-r/bulk-translate
content.raw: https://github.com/nicolay-r/bulk-translate
content.type: link
content.type: new_line
content.raw: 🌌 nlp-thirdgate: 
content.type: text
content.value: 🌌 nlp-thirdgate: 
content.href: https://github.com/nicolay-r/nlp-thirdgate?tab=readme-ov-file
content.raw: https://github.com/nicolay-r/nlp-thirdgate?tab=readme-ov-file
content.type: link
rawContent: 📢 If you're looking for translating massive dataset of JSON-lines / CSV data with various set of source fields, then the following update would be relevant. So far and experimenting with adapting language specific Sentiment Analysis model, got a change to reforge and relaese bulk-translate 0.25.2.
  ⭐️ https://github.com/nicolay-r/bulk-translate/releases/tag/0.25.2
  
  The update has the following major features
  - Supporting schemas: all the columns to be translated are now could be declared within the same prompt-style format. using json this automatically allows to map them onto output fields
  - The related updates for shell execution mode: schema parameter is now available alongside with just a prompt usage before.
  
  Benefit is that your output is invariant. You can extend and stack various translators with separated shell laucnhes.
  
  Screenshot below is the application of the google-translate engine in manual batching mode.
  🚀 Performance: 2.5 it / sec (in the case of a single field translation)
  
  🌟 about bulk-translate: https://github.com/nicolay-r/bulk-translate
  🌌 nlp-thirdgate: https://github.com/nicolay-r/nlp-thirdgate?tab=readme-ov-file
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