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Prikvačeni tweet
We've done a few benchmarks to our
/Transformers library! we compare 10 architectures for inference, with PyTorch and TensorFlow.
We further benchmark them with TorchScript and XLA!
The results are detailed in the first of a series of blog posts:https://medium.com/huggingface/benchmarking-transformers-pytorch-and-tensorflow-e2917fb891c2 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Hi world! I'm excited to start working
@huggingface in Paris as a research engineer this week :)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Facebook AI's latest research on multimodal bitransformers is the first multimodal model to be part of the
@HuggingFace library! Released here:https://github.com/huggingface/transformers/releases …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Hello Twitterverse
Started my second day as Chief of Staff at @huggingface
& I'm so excited to delve into the world of NLP.
My favorite use case of Transformers
:https://twitter.com/huggingface/status/1205547602529284097?s=20 …
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A few people asked us to talk more about our model sharing feature, so here goes:pic.twitter.com/OXPJvU5dy0
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Guest blog post from
@huggingface angel investor@madlag on sparse tensors in neural nets. I am VERY excited by what's going to happen in sparsity-land this year
https://medium.com/huggingface/is-the-future-of-neural-networks-sparse-an-introduction-1-n-d03923ecbd70 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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The 2.4.0 release of transformers is **𝐌𝐀𝐒𝐒𝐈𝐕𝐄** thanks to our amazing community of contributors.
https://github.com/huggingface/transformers/releases/tag/v2.4.0 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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I'm impressed by the work Hugging Face is doing.https://twitter.com/ClementDelangue/status/1223747179480780800 …
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Transformers 2.4.0 is out
- Training transformers from scratch is now supported
- New models, including *FlauBERT*, Dutch BERT, *UmBERTo*
- Revamped documentation
- First multi-modal model, MMBT from @facebookai, text & images Bye bye Python 2
https://github.com/huggingface/transformers/releases …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Thanks
@FirstMarkCap@mattturck for the invitation to talk about why I believe NLP is the most important field of Machine Learning. Who doesn't agree with me?https://firstmarkcap.com/events/data-driven/nlp-the-most-important-field-of-ml/ …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Do you speak French?
If you do, you should watch the interesting discussion we had with the awesome @ThiboNeveu on "Podcast IA" – sharing this, even though it's always weird to listen to one's voice on video
https://www.youtube.com/watch?v=RL8QQk-LJp8 …pic.twitter.com/B2DZlSKB0c
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Let me highlight this amazing work I've read recently on
#compositionality in NLP, in which you'll find both: - a deep discussion of what it means for a neural model to be compositional - a deep and insightful comparison of LSTM, ConvNet & Transformers!
https://arxiv.org/abs/1908.08351 pic.twitter.com/LX9JQE1Ira
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As you may know, we just raised our series A. It wouldn't have been possible without the help and contribution of the fantastic
#NLProc community that we serve. So join us next week to celebrate in NYC around craft beers & classic video games!

https://www.eventbrite.com/e/hugging-face-nlp-community-party-registration-86625931493 …pic.twitter.com/8RCnuJ3kyd
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Now that neural nets have fast implementations, a bottleneck in pipelines is tokenization: strings
model inputs.
Welcome
Tokenizers: ultra-fast & versatile tokenization led by @moi_anthony: -encode 1GB in 20sec -BPE/byte-level-BPE/WordPiece/SentencePiece... -python/js/rust...pic.twitter.com/1TfJ1Hm1xx
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At the Paris office. Who’s there?
#NLProc@LysandreJik@MorganFuntopic.twitter.com/bMRaNJZ2EB – mjesto: Station F
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It's January 1st, which means...

we can FINALLY leave Python 2 behind!! 
pic.twitter.com/jaIPDTMpBw
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So awesome to see the community effort on multi-lingual NLP! In the past month, models in Dutch, Finnish, French, German, Italian, Japanese, Mandarin and Spanish have been added to transformers. Check them all here: https://huggingface.co/models pic.twitter.com/DooTvFx6Ow
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┏━━┓┏━━┓┏━━┓┏━━┓ ┗━┓┃┃┏┓┃┗━┓┃┃┏┓┃ ┏━┛┃┃┃┃┃┏━┛┃┃┃┃┃ Solving Natural Language Processing! ┃┏━┛┃┃┃┃┃┏━┛┃┃┃┃ ┃┗━┓┃┗┛┃┃┗━┓┃┗┛┃ ┗━━┛┗━━┛┗━━┛┗━━┛
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If you're using Transformers from source, we've rolled out 2 nice beta features (TBR in January)
Ultra-fast Bert/GPT2 tokenizers (up to 80x faster)
Easy/versatile sequence generation for generative models: top-k/nucleus/temperature sampling, penalized/greedy, beam search...pic.twitter.com/KNAmDbQPk3
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We spend our time finetuning models on tasks like text classif, NER or question answering. Yet
Transformers had no simple way to let users try these fine-tuned models.
Release 2.3.0 brings Pipelines: thin wrappers around tokenizer + model to ingest/output human-readable data.pic.twitter.com/ZcPTXOJsuS
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