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$40M series B! 🙏Thank you open source contributors, pull requesters, issue openers, notebook creators, model architects, twitting supporters & community members all over the 🌎!
We couldn't do what we do & be where we are - in a field dominated by big tech - without you!
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The new SOTA is in Transformers! DeBERTa-v2 beats the human baseline on SuperGLUE and up to a crazy 91.7% dev accuracy on MNLI task.
Beats T5 while 10x smaller!
DeBERTa-v2 contributed by @Pengcheng2020 from @MSFTResearch
Try it directly on the hub: huggingface.co/microsoft/debe…
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🚨Transformers is expanding to Speech!🚨
🤗Transformers v4.3.0 is out and we are excited to welcome @FacebookAI's Wav2Vec2 as the first Automatic Speech Recognition model to our library!
👉Now, you can transcribe your audio files directly on the hub: huggingface.co/facebook/wav2v…
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🔥We're launching the new huggingface.co and it's incredible
🚀Play live with +10 billion parameters models, deploy them instantly in production with our hosted API, join the 500 organizations using our hub to host/share models & datasets
And one more thing... 👇
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Fine-tuning a *3-billion* parameter model on a single GPU?
Now possible in transformers, thanks to the DeepSpeed/Fairscale integrations!
Thank you @StasBekman for the seamless integration, and thanks to @Microsoft and @FacebookAI teams for their support!
huggingface.co/blog/zero-deep…
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Release alert: the 🤗datasets library v1.2 is available now!
With:
- 611 datasets you can download in one line of python
- 467 languages covered, 99 with at least 10 datasets
- efficient pre-processing to free you from memory constraints
Try it out at:
github.com/huggingface/da…
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We are honored to be awarded the Best Demo Paper for "Transformers: State-of-the-Art Natural Language Processing" at #emnlp2020 😍
Thank you to our wonderful team members and the fantastic community of contributors who make the library possible 🤗🤗🤗
aclweb.org/anthology/2020…
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Our API now includes a brand new pipeline: zero-shot text classification
This feature lets you classify sequences into the specified class names out-of-the-box w/o any additional training in a few lines of code! 🚀
Try it out (and share screenshots 📷): huggingface.co/facebook/bart-…
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The ultimate guide to encoder-decoder models!
Today, we're releasing part one explaining how they work and why they have become indispensable for NLG tasks such as summarization and translation.
> colab.research.google.com/drive/18ZBlS4t…
Subscribe for the full series: huggingface.curated.co
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🔥Transformers' first-ever end-2-end multimodal demo was just released, leveraging LXMERT, SOTA model for visual Q&A!
Model by @HaoTan5, @mohitban47, with an impressive implementation in Transformers by @avalmendoz (@uncnlp)
Notebook available here: colab.research.google.com/drive/18TyuMfZ… 🤗
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Want speedy transformers models w/o a GPU?! 🧐
Starting with transformers v3.1.0 your models can now run at the speed of light on commodity CPUs thanks to ONNX Runtime quantization!🚀. Check out our 2nd blog post with ONNX Runtime on the subject! 🔥
medium.com/microsoftazure…
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Transformers v3.1.0 is out, first pypi release with 💫 PEGASUS, DPR, mBART 💫
📖 New & simpler docs and tutorials
🎤 Dialogue & zero-shot pipelines
⭐️ New encoder-decoder architectures: Bert2GPT2, Roberta2Roberta, Longformer2Roberta, ...
📕 Named outputs:
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No labeled data? No problem.
The 🤗 Transformers master branch now includes a built-in pipeline for zero-shot text classification, to be included in the next release.
Try it out in the notebook here: colab.research.google.com/drive/1jocViLo…
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