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#opensource is more than just public code. It's a mindset of sharing, being transparent and collaborating across organizations. It's about building on the shoulders of other projects and advancing together the state of technology (1/N)@huggingface,@spacy_io,@fastdotai,#NLPpic.twitter.com/YkGjDU6sHu
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Today's
#NLP is heavily fueled by the power of#GPUs. Glad to announce that we are now a member of@NVIDIA's Inception program! Looking forward to even more GPU power and acceleration of our models via#apex & co@NvidiaAI#NLP#cuda#amp#deeplearningpic.twitter.com/IHG90MzMbr
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It's challenging to keep track of all the latest
#languagemodels out there. What was again the difference between#RoBERTa and#BERT? What's the core idea behind#T5? Here's a little (not comprehensive)#cheatsheet that we use for workshops#nlp#NLProc#deeplearningpic.twitter.com/KxBSWv8OTd
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As promised: here are the slides from Malte's talks in Warsaw! - Keynote at
@pydatawarsaw: https://drive.google.com/file/d/1V81Vn5n5L0z8naiu3tnZfTwt5CUj1Ofp/view?usp=sharing … - Talk at HumanTech: https://drive.google.com/file/d/1uQM3nEGkJh_HWpWJ4TV_FwGDTyCY3MBf/view?usp=sharing … Reach out to us if you have some large polish text data set (> 10GB) and want to train a polish BERT or ALBERT.pic.twitter.com/noyQpfqzeh
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Glad that so many interested people gathered today at the ML Meetup in Berlin. You can find the slides of Branden's and Timo's talk about
#transferlearning here: http://bit.ly/2NCTdey pic.twitter.com/JynMJsAW77
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We just released FARM 0.2.0 - making
#transferlearning faster & easier: -
Significant speed up of preprocessing & training
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More user friendly processors for custom datasets
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Several bug fixes
Check it out: https://github.com/deepset-ai/FARM/releases/tag/0.2.0 …pic.twitter.com/HR8g9JlGTc
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Excited to open-source
#FARM - our internal framework for#transferlearning. FARM makes it easy to get benefits from SOTA language models like#BERT for your own#NLP task (NER, QA...). Try it out! Code: https://github.com/deepset-ai/FARM Docs: https://farm.deepset.ai/ From Berlin with
pic.twitter.com/DG07aoxlAM
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Inspiring talk by
@seb_ruder at#spaCyIRL stressing the importance of#opensource in#transferlearning. Totally in line with our beliefs and a reason why we open sourced German#BERT + will continue with our#transferlearning framework soon.pic.twitter.com/3ya7pKp5UT
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Today we are excited to
#opensource our#German#BERT model that significantly outperforms@GoogleAI's multilingual model in 4 of 5 German downstream tasks and therefore enables a performance boost for NLP on German text! More: https://deepset.ai/german-bert#NLP#ML#TransferLearningpic.twitter.com/Goi7tVu89R
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Our Co-Founder Timo explaining
#NLP and why it helps in fulfilling#BigData's promises at yesterday's "StartupBBQ". Thanks to@InVisionDE Group for providing a wonderful experience at their office and to@STARTPLATZ for the organization.#machinelearning#nobullshitpic.twitter.com/x2wBxr4DgL
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As promised, you can now download the slides from
@malte_pietsch's talk at#Pawcon about Named Entity Recognition: https://goo.gl/PKB77C . You will find all articles and code repos mentioned during the talk. Highly recommended resources if you like to get deeper into the topicpic.twitter.com/v0CoY5A45Q
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What's the role of a
#deeplearning engineer? Today, Malte shared his perspective on involved tasks, challenges and career paths in an interview at@StackFuelHQ. Thanks again for the invitation!pic.twitter.com/gWrurIm4Bo
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Today we pitched at the demo day of
@BerlinerSpk at@theplaceberlin. Incredible, how much has happened with deepset since our last pitch there in February. Exciting times!pic.twitter.com/cuz4pTmdvg
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Inspiring work on MAC cells - a new
#neuralnetwork architecture designed for machine reasoning.#iclr2018https://youtu.be/24AX4qJ7Tts -
Our Timo Möller won the knowledge extraction challenge of
#aihack from#Telekom with a NLP model for customer support requests. Congrats!pic.twitter.com/0WJ4SClInA
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