metadata

license: mit
language:
  - de
tags:
  - title generation
  - headline-generation
  - teaser generation
  - keyword generation
  - tweet generation
  - news
inference: false

snip-igel-10

snip-igel-10 Version 1.0 / 13 April 2023

An adapter for IGEL to generate german news snippets with human written instructions

See snip-igel-500 for the full model description. We repeated fine-tuning with gradually increased amounts of training data, to see the difference.

Environmental Impact

Carbon emissions were estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Hardware Type: RTX 4090
Hours used: 1min 59s
Cloud Provider: Vast.ai
Compute Region: Poland
Carbon Emitted: ~0.05 kg of CO2e