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Updated credits w nvidia and arrow

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@@ -44,7 +44,9 @@ Trained by using the approach outlined in the paper **LLM2Vec: Large Language Mo
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  LoRa Finetuning 1000 steps of MNTP on cleaned Danish Wikipedia https://huggingface.co/datasets/jealk/wiki40b-da-clean
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  LoRa Finetuning 1000 steps of SimCSE on sentences from Scandivian Wikipedia (da, nn, nb, sv, fo, is): https://huggingface.co/datasets/jealk/scandi-wiki-combined (*Sentence subset*)
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- Credits for code-repo used to finetune this model https://github.com/McGill-NLP/llm2vec
 
 
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  Requires the llm2vec package to encode sentences. Credits to https://huggingface.co/McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised for the below instructions:
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  LoRa Finetuning 1000 steps of MNTP on cleaned Danish Wikipedia https://huggingface.co/datasets/jealk/wiki40b-da-clean
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  LoRa Finetuning 1000 steps of SimCSE on sentences from Scandivian Wikipedia (da, nn, nb, sv, fo, is): https://huggingface.co/datasets/jealk/scandi-wiki-combined (*Sentence subset*)
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+ Credits for code-repo used to finetune this model https://github.com/McGill-NLP/llm2vec .
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+ Thanks to **Arrow Denmark** and **Nvidia** for sponsoring the compute used to train this model.
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  Requires the llm2vec package to encode sentences. Credits to https://huggingface.co/McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised for the below instructions:
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