GE

GEITje-7B – A New Large Open Dutch Language Model

Hacker News

GEITje-7B – A New Large Open Dutch Language Model

Tried my hand at training a large open Dutch language model, for which the pickings are slim right now. GEITje is a large open Dutch language model with 7 billion parameters, based on Mistral 7B. I've continued pretraining it on 10 billion tokens of Dutch text. This has improved its Dutch language skills and increased its knowledge of Dutch topics. There's an experimental chat-finetuned model too, called GEITje-chat. I have to say the experience of gathering a dataset and training a model has been very educational for me. Being forced to deal with every detail yourself really deepens your understanding of a subject. It's all in the hands of the community now. Can't wait to see what they do with it! Want to try it out? There's a demo live at Hugging Face Spaces right now: https://huggingface.co/spaces/Rijgersberg/GEITje-7B-chat

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, open · Missing: mac, agents, macos
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: para, education · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

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