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

# snip-igel-10

<!-- Provide a quick summary of what the model is/does. -->

snip-igel-10
Version 1.0 / 13 April 2023

An adapter for [IGEL](https://huggingface.co/philschmid/instruct-igel-001) to generate german news snippets with human written instructions

See [snip-igel-500](https://huggingface.co/snipaid/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](https://mlco2.github.io/impact/#compute) 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