Hugging Face @huggingface Twitter profile

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Hugging Face

1 year

🤗 Transformers has been built by, with, and for the community. Reaching 100k ⭐ on GitHub is a testament to ML's reach and the community's will to innovate and contribute. To celebrate, we highlight 100 incredible projects in transformers' vicinity.

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Hugging Face

@huggingface

1 year

We just released Transformers' boldest feature: Transformers Agents. This removes the barrier of entry to machine learning Control 100,000+ HF models by talking to Transformers and Diffusers Fully multimodal agent: text, images, video, audio, docs...🌎

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Hugging Face

@huggingface

2 years

🤗🚀

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Hugging Face

@huggingface

9 months

Llama 2: Now on Hugging Chat 🤗🦙 Try out the 70B Chat model for free with super fast inference, web search, and powered by open-source tools! 👉

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Hugging Face

@huggingface

1 year

THIS IS BIG! 👀 It's now possible to take any of the >30,000 ML apps from Spaces and run them locally (or on your own infrastructure) with the new "Run with @Docker " feature. 🔥🐳 See an app you like? Run it yourself in just 2 clicks🤯

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Hugging Face

@huggingface

4 years

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:

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Hugging Face

@huggingface

3 years

The first part of the Hugging Face Course is finally out! Come learn how the 🤗 Ecosystem works 🥳: Transformers, Tokenizers, Datasets, Accelerate, the Model Hub! Share with your friends who want to learn NLP, it's free! Come join us at

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Hugging Face

@huggingface

3 years

🚨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:

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Hugging Face

@huggingface

1 year

SAM, the groundbreaking segmentation model from @Meta is now in available in 🤗 Transformers! What does this mean? 1. One line of code to load it, one line to run it 2. Efficient batching support to generate multiple masks 3. pipeline support for easier usage More details: 🧵

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Hugging Face

@huggingface

3 years

$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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Hugging Face

@huggingface

8 months

Code Llama: Now on Hugging Chat 💻🦙 Try out the 34B Instruct model for free with super fast inference! 👉

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Hugging Face

@huggingface

3 years

Last week, EleutherAI released two checkpoints for GPT Neo, an *Open Source* replication of OpenAI's GPT-3 These checkpoints, of sizes 1.3B and 2.7B are now available in🤗Transformers! The generation capabilities are truly🤯, try it now on the Hub:

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Hugging Face

@huggingface

2 years

Last week @MetaAI publicly released huge LMs, with up to ☄️30B parameters. Great win for Open-Source🎉 These checkpoints are now in 🤗transformers! But how to use such big checkpoints? Introducing Accelerate and ⚡️BIG MODEL INFERENCE⚡️ Load & USE the 30B model in colab (!)⬇️

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Hugging Face

@huggingface

1 year

The first RNN in transformers! 🤯 Announcing the integration of RWKV models in transformers with @BlinkDL_AI and RWKV community! RWKV is an attention free model that combines the best from RNNs and transformers. Learn more about the model in this blogpost:

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Hugging Face

@huggingface

4 years

Let’s democratize NLP for all languages! 🌎🌎🌎 Today, with v2.9.1, we are releasing 1,008 machine translation models, covering ` of 140 different languages trained by @jorgtiedemann with @marian , ported by @sam_shleifer . Find your language here: [1/4]

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Hugging Face

@huggingface

4 years

𝗢𝗨𝗥 𝗗𝗘𝗙𝗜𝗡𝗜𝗧𝗜𝗩𝗘 𝗧𝗨𝗧𝗢𝗥𝗜𝗔𝗟 🔥 How to train a new language model from scratch using Transformers and Tokenizers ➡️

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Hugging Face

@huggingface

7 months

How to train a Llama 2 chatbot (a step-by-step guide, designed for non-coders)

Non-engineers guide: Train a LLaMA 2 chatbot

huggingface.co

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Hugging Face

@huggingface

4 years

Long-range sequence modeling meets 🤗 transformers! We are happy to officially release Reformer, a transformer that can process sequences as long as 500.000 tokens from @GoogleAI . Thanks a million, Nikita Kitaev and @lukaszkaiser ! Try it out here:

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Hugging Face

@huggingface

3 years

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 🤗🤗🤗

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Hugging Face

@huggingface

4 years

Time to push explainable AI 🔬 exBERT, the visual analysis tool to explore learned representations from @MITIBMLab is now integrated on our model pages for BERT, DistilBERT, RoBERTa, XLM & more! Just click on the tag #exbert on @huggingface ’s models page:

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Hugging Face

@huggingface

2 years

日本からの嬉しいお知らせです！rinnaが日本語で学習したJapanese Stable DiffusionがHugging Face Spacesでデモ化されました！

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Hugging Face

@huggingface

3 years

🤗 Transformers meets VISION 📸🖼️ v4.6.0 is the first CV dedicated release! - CLIP @OpenAI , Image-Text similarity or Zero-Shot Image classification - ViT @GoogleAI , and - DeiT @facebookai , SOTA Image Classification Try ViT/DeiT on the hub (Mobile too!):

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Hugging Face

@huggingface

2 years

🧨Diffusion models have been powering impressive ML apps, enabling DALL-E or Imagen Introducing 🤗 diffusers: a modular toolbox for diffusion techniques, with a focus on: 🚄Inference pipelines ⏰Schedulers 🏭Models 📃Training examples

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Hugging Face

@huggingface

4 years

Introducing PruneBERT, fine-*P*runing BERT's encoder to the size of a high-resolution picture (11MB) while keeping 95% of its original perf! Based on our latest work on movement pruning: Code and weights:

huggingface/prunebert-base-uncased-6-finepruned-w-distil-squad · Hugging Face

huggingface.co

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Hugging Face

@huggingface

4 years

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...

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Hugging Face

@huggingface

10 months

We are looking into an incident where a malicious user took control over the Hub organizations of Meta/Facebook & Intel via reused employee passwords that were compromised in a data breach on another site. We will keep you updated 🤗

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Hugging Face

@huggingface

9 months

Hugging Face is now part of the PyTorch Foundation as a premier member 🤝 We have been collaborating with the PyTorch team for the past four years and are committed to supporting the project. We share an objective: to lower the barrier of entry to ML.

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Hugging Face

@huggingface

1 year

Hugging Faceから日本へのお知らせです！ Hugging Faceコースの日本語翻訳を始めました。東北大学のStudent Ambassadorsの皆さんのお陰で第一章の翻訳が終了しました。今後もコツコツと翻訳していきます。是非コースを読んでHugging Face Tranformersについて学んで、使ってみてください！

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Hugging Face

@huggingface

4 years

🤗Transformers v3.0 is out🔥 — [1/4]

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Hugging Face

@huggingface

4 years

Bored at home? Need a new friend? Hang out with BART, the newest model available in transformers (thx @sam_shleifer ) , with the hefty 2.6 release (notes: ). Now you can get state-of-the-art summarization with a few lines of code: 👇👇👇

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Hugging Face

@huggingface

3 years

EleutherAI's GPT-J is now in 🤗 Transformers: a 6 billion, autoregressive model with crazy generative capabilities! It shows impressive results in: - 🧮Arithmetics - ⌨️Code writing - 👀NLU - 📜Paper writing - ... Play with it to see how powerful it is:

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Hugging Face

@huggingface

4 years

Transformers v2.2 is out, with *4* new models and seq2seq capabilities! ALBERT is released alongside CamemBERT, implemented by the authors, DistilRoBERTa (twice as fast as RoBERTa-base!) and GPT-2 XL! Encoder-decoder with ⭐Model2Model⭐ Available on

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Hugging Face

@huggingface

1 year

Today we are excited to announce a new partnership with @awscloud ! 🔥 Together, we will accelerate the availability of open-source machine learning 🤝 Read the post 👉

Hugging Face and AWS partner to make AI more accessible

huggingface.co

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Hugging Face

@huggingface

3 years

Document parsing meets 🤗 Transformers! 📄 #LayoutLMv2 and #LayoutXLM by @MSFTResearch are now available! 🔥 They're capable of parsing document images (like PDFs) by incorporating text, layout, and visual information, as in the @gradio demo below ⬇️

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Hugging Face

@huggingface

5 years

🥁🥁🥁 Welcome to "pytorch-transformers", the 👾 library for Natural Language Processing!

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Hugging Face

@huggingface

4 years

The 101 for text generation! 💪💪💪 This is an overview of the main decoding methods and how to use them super easily in Transformers with GPT2, XLNet, Bart, T5,... It includes greedy decoding, beam search, top-k/nucleus sampling,...: by @PatrickPlaten

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Hugging Face

@huggingface

4 years

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 🙃

Releases · huggingface/transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - huggingface/transformers

github.com

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Hugging Face

@huggingface

3 years

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!

Fit More and Train Faster With ZeRO via DeepSpeed and FairScale

huggingface.co

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Hugging Face

@huggingface

4 years

┏━━┓┏━━┓┏━━┓┏━━┓ ┗━┓┃┃┏┓┃┗━┓┃┃┏┓┃ ┏━┛┃┃┃┃┃┏━┛┃┃┃┃┃ Solving Natural Language Processing! ┃┏━┛┃┃┃┃┃┏━┛┃┃┃┃ ┃┗━┓┃┗┛┃┃┗━┓┃┗┛┃ ┗━━┛┗━━┛┗━━┛┗━━┛

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Hugging Face

@huggingface

4 years

You can now visualize Transformers training performance with a seamless @weights_biases integration. Compare hyperparameters, output metrics, and system stats like GPU utilization across your models! Step-by-step guide: Colab:

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Hugging Face

@huggingface

5 years

💃PyTorch-Transformers 1.1.0 is live💃 It includes RoBERTa, the transformer model from @facebookai , current state-of-the-art on the SuperGLUE leaderboard! Thanks to @myleott @julien_c @LysandreJik and all the 100+ contributors!

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Hugging Face

@huggingface

1 year

It's been an exciting year for 🤗Transformers. We tripled the number of weekly active users over 2022, with over 1M users most weeks now and 300k daily pip installs on average🤯

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Hugging Face

@huggingface

4 years

🚨New release alert 🚨BERT, RoBERTa, GPT2, TransformerXL and most of the community models are now an order of magnitude faster thanks to the integration of the tokenizers library! Check it out here:

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Hugging Face

@huggingface

3 years

🔥Fine-Tuning @facebookai 's Wav2Vec2 for Speech Recognition is now possible in Transformers🔥 Not only for English but for 53 Languages🤯 Check out the tutorials: 👉 Train Wav2Vec2 on TIMIT 👉 Train XLSR-Wav2Vec2 on Common Voice

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Hugging Face

@huggingface

2 years

The Technology Behind BLOOM Training🌸 Discover how @BigscienceW used @MSFTResearch DeepSpeed + @nvidia Megatron-LM technologies to train the World's Largest Open Multilingual Language Model (BLOOM):

The Technology Behind BLOOM Training

huggingface.co

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Hugging Face

@huggingface

4 years

GPT-3 from @OpenAI got you interested in zero-shot and few-shot learning? You're lucky because our own @joeddav has just released a demo of zero-shot topic classification! Test how the model can predict a topic it has NEVER been trained on: 🤯🤯🤯

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Hugging Face

@huggingface

4 years

How big should my language model be? As NLP researchers and practitioners, that question is central. We have built a tool that calculates an optimal model size and training time for your budget so you don't have to. See it in action at ! [1/2]

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Hugging Face

@huggingface

4 years

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.

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Hugging Face

@huggingface

4 years

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! 🔥

Faster and smaller quantized NLP with Hugging Face and ONNX Runtime

Popular Hugging Face Transformer models (BERT, GPT-2, etc) can be shrunk and accelerated with ONNX Runtime quantization without retraining.

medium.com

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Hugging Face

@huggingface

2 months

We're having some infra issues; we're working on it. Please send hugs! 🤗 In the meantime, import os os.environ['HF_HUB_OFFLINE']=1

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Hugging Face

@huggingface

2 years

💫 Perceiver IO by @DeepMind is now available in 🤗 Transformers! A general purpose deep learning model that works on any modality and combinations thereof 📜text 🖼️ images 🎥 video 🔊 audio ☁️ point clouds ... Read more in our blog post:

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Hugging Face

@huggingface

3 years

🔥We're launching the new 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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Hugging Face

@huggingface

3 years

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:

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Hugging Face

@huggingface

2 years

🖌️ Stable Diffusion meets 🧨Diffusers! Releasing diffusers==0.2.2 with full support of @StabilityAI 's Stable Diffusion & schedulers 🔥 Google colab: 👉 Code snippet 👇

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Hugging Face

@huggingface

4 years

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. > Subscribe for the full series:

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Hugging Face

@huggingface

4 months

Hugging Face 🫶 @GoogleColab With the latest release of huggingface_hub, you don't need to manually log in anymore. Create a secret once and share it with every notebook you run. 🤗 pip install --upgrade huggingface_hub Check it out!👇

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Hugging Face

@huggingface

4 years

Today we're happy to release four new official notebook tutorials available in our documentation and in colab thanks to @MorganFunto to get started with tokenizers and transformer models in just seconds! (1/6)

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Hugging Face

@huggingface

4 years

The 1.5 billion parameter GPT-2 (aka gpt2-xl) is up: ✅ in the transformers repo: ✅ try it out live in Write With Transformer🦄 Coming next: 🔘 Detector model based on RoBERTa Thanks @OpenAI @Miles_Brundage @jackclarkSF and all

Write With Transformer

transformer.huggingface.co

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Hugging Face

@huggingface

5 years

This is SO meta 🤓 We trained a generative language model on a dataset of ArXiv NLP papers. You can now get a neural net to write your papers for (with?) you 🔥. We heard from a few researchers that they're already using it in submitted papers.

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Hugging Face

@huggingface

2 years

Transformers v4.22 is out, and includes the first VIDEO models! 🎥 💥VideoMAE: masked auto-encoders for video 💥X-CLIP: CLIP for video-language Other nice goodies: 💥Swin Transformer v2 💥Pegasus-X 💥Donut 💥MobileViT ... and MacOS support (device="mps")!

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Hugging Face

@huggingface

9 months

TRL 🤗 Hugging Face Excited to announce that we're doubling down on our efforts to democratize RLHF and reinforcement learning with TRL, new addition to the @huggingface family, developed and led by team member @lvwerra 🎉🎉 Train your first RLHF model 👉

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Hugging Face

@huggingface

3 years

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:

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Hugging Face

@huggingface

7 months

Zephyr 7b beats Llama 70b on MT Bench 🤯🤯🤯

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Hugging Face

@huggingface

3 years

🔥JAX meets Transformers🔥 @GoogleAI 's JAX/Flax library can now be used as Transformers' backbone ML library. JAX/Flax makes distributed training on TPU effortless and highly efficient! 👉 Google Colab: 👉 Runtime evaluation:

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Hugging Face

@huggingface

4 years

1/4. Four NLP tutorials are now available on @kaggle ! It's now easier than ever to leverage tokenizers and transformer models like BERT, GPT2, RoBERTa, XLNet, DistilBERT,... for your next competition! 💪💪💪! #NLProc #NLP #DataScience #kaggle

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Hugging Face

@huggingface

11 months

📣 Calling all game dev and AI enthusiasts!🎮 Already 400 people signed up for the first Open Source AI Game Jam, where you'll use AI tools to make a game in a weekend🔥 Sign up here 👉 What AI tools? Let's focus today on Audio tools 🔊 ⬇️

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Hugging Face

@huggingface

2 months

The Open Source community is amazing 🤗

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Hugging Face

@huggingface

3 years

We've heard your requests! Over the past few months ... we've been working on a Hugging Face Course! The release is imminent. Sign-up for the newsletter to know when it comes out: Sneak peek; Transfer Learning with @GuggerSylvain :

What is Transfer Learning?

What is transfer learning, why and when is it useful?This video is part of the Hugging Face course: http://huggingface.co/courseOpen in colab to run the code...

www.youtube.com

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Hugging Face

@huggingface

2 years

Scikit-Learn and 🤗 join forces! With a growing number of tabular classification & regression checkpoints, we believe statistical ML has its place on the HF Hub. We're excited to partner with sklearn, statistical ML champion, and move forward together.

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Hugging Face

@huggingface

3 years

GPT-Neo, the #OpenSource cousin of GPT3, can do practically anything in #NLP from sentiment analysis to writing SQL queries: just tell it what to do, in your own words. 🤯 How does it work? 🧐 Want to try it out? 🎮 👉

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Hugging Face

@huggingface

4 years

Thanks to @srush_nlp , we now have an example of a training module for NER leveraging transformers. Under 300 lines of codes and supports GPUs and TPUs thanks to @PyTorchLightnin ! Colab: Example:

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Hugging Face

@huggingface

2 years

Transformers v4.13.0 is out and it is *big*: Vision: - 🖼️ SegFormer - 🖨️ ImageGPT Audio: - 🔡 Language model support for ASR Multimodal: - ⚖️ Vision-Text dual encoders NLP: - 🔣 mLUKE - 🏅 DeBERTa-v3 Trainer: - 1⃣6⃣ The Trainer now supports BF16/TF32! 🌠New doc frontend 🌠

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@huggingface

4 years

🔥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: 🤗

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@huggingface

2 years

Open Source

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Hugging Face

@huggingface

2 years

TODAY'S A BIG DAY Spaces are now publicly available Build, host, and share your ML apps on @huggingface in just a few minutes. There's no limit to what you can build. Be creative, and share what you make with the community. 🙏 @streamlit and @gradio

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Hugging Face

@huggingface

4 years

👋 To all JS lovers: NLP is more accessible than ever! You can now leverage the power of DistilBERT-cased for Question Answering w/ just 3 lines of code!!! 🤗 You can even run the model remotely w/ the built-in @TensorFlow Serving compatibility 🚀

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@huggingface

10 months

At Hugging Face, we are working to enable you to easily build and serve your own LLMs 🧑‍💻👨‍💻👩‍💻 In this blog, we talk about the amazing world of open-source LLMs, the challenges, and how the Hugging Face ecosystem can help you 🪐 Read about them here 👉

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Hugging Face

@huggingface

3 years

🥁 We can't wait to share our new inference product with you! 🤩 - it achieves 1ms latency on Transformer models 🏎 - you can deploy it in your own infrastructure ⚡️ - we call it: 🤗 Infinity 🚀 📅 Join us for a live event and demo on 9/28!

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Hugging Face

@huggingface

3 years

We're thrilled to partner with to create some great new content for their NLP Specialization on Coursera! With this update, you can access exciting new material and lectures that cover the state of the art in NLP 🧑‍🏫

Natural Language Processing

Offered by deeplearning.ai. Natural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the most broadly applied areas of machine learni...

www.coursera.org

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Hugging Face

@huggingface

4 years

Happy to officially include DialoGPT from @MSFTResearch to 🤗transformers (see docs: ) DialoGPT is the first conversational response model added to the library. Now you can build a state-of-the-art chatbot in just 10 lines of code 👇👇👇

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@huggingface

5 years

Our Distilbert paper just got accepted at NeurIPS 2019's ECM2 workshop! - 40% smaller 60% faster than BERT - 97% of the performance on GLUE We also distilled GPT2 in an 82M params model💥 All the weights are available in TF2.0 @tensorflow here:

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Hugging Face

@huggingface

4 years

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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Hugging Face

@huggingface

2 years

Last week, @MetaAI introduced NLLB-200: a massive translation model supporting 200 languages. Models are now available through the Hugging Face Hub, using 🤗Transformers' main branch. Models on the Hub: Learn about NLLB-200:

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Hugging Face

@huggingface

2 years

Machine learning demos are increasingly a vital part of releasing a model. Demos allow anyone, not just ML engineers, to try a model, give feedback on predictions, and build trust That's why we are thrilled to announce @Gradio 3.0: a grounds-up redesign of the Gradio library 🥳

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Hugging Face

@huggingface

3 years

🤗Transformers are starting to work with structured databases! We just released 🤗Transformers v4.1.1 with TAPAS, a multi-modal model for question answering on tabular data from @googleAI . Try it out through transformers or our inference API:

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Hugging Face

@huggingface

11 months

🚨Exciting news! Next week, we’ll be launching a brand-new Audio Course! 🤗 Sign up today () and join us for a LIVE course launch event featuring amazing guests like @DynamicWebPaige , Seokhwan Kim, and @functiontelechy ! ⚡️

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Hugging Face

@huggingface

4 years

Happy to announce we partenered with @onnxai @onnxruntime @microsoft to make state-of-the-art inference up to 5x faster 🚀. NLP for every people and organizations! #msbuild

Accelerate your NLP pipelines using Hugging Face Transformers and ONNX Runtime

This post was written by Morgan Funtowicz from Hugging Face and Tianlei Wu from Microsoft

medium.com

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Hugging Face

@huggingface

3 years

🤗We are going to invest more in @tensorflow in 2021! If you want to take part in building the fastest growing NLP open-source library, join us:

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Hugging Face

@huggingface

4 years

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 📷):

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Hugging Face

@huggingface

3 years

20,000+ machine learning models connected to 3,000+ apps? Hugging Face meets Zapier! 🤯🤯🤯 With the Hugging Face API, you can now easily connect models right into apps like Gmail, Slack, Twitter, and more: [1/2]

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Hugging Face

@huggingface

1 year

🧨Diffusers supports Stable Diffusion 2 ! Run @StabilityAI 's Stable Diffusion 2 with zero changes to your code using your familiar diffusers API. Everything is supported: attention optimizations, fp16, img2image, swappable schedulers, and more🤗

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Hugging Face

@huggingface

2 months

We're excited to collaborate with the Europan Space Agency for the release of MajorTOM, the largest ML-ready Sentinel-2 images dataset! 🚀 It covers 50% of the Earth. 2.5 trillion pixels of open source! 🤗👐🌌🚀🌏

Major-TOM (Major TOM)

huggingface.co

European Space Agency

@esa

2 months

Our @ESA_EO Φ-lab has released, in partnership with @huggingface , the first dataset of 'MajorTOM', or the Terrestrial Observation Metaset, the largest community-oriented and machine-learning-ready collection of @CopernicusEU #Sentinel2 images ever published and covering over 50%…

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Hugging Face

@huggingface

3 years

🚨 NEW MODEL ALERT 🚨 Translate text to, or between 50 languages with mBART-50 from @facebookai ! 🇺🇳 One-to-Many model: translate from English to 49 other languages ↔️ Many-to-Many model: translation btw any pair of 50 languages

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Hugging Face

@huggingface

4 years

Transformers v2.9 is out, with a built-in Trainer and TFTrainer 🔥 This let us reorganize the example scripts completely for a cleaner codebase. - Same user-facing API for PyTorch and TF 2 - Support for GPU, Multi-GPU, and TPU - Easier than ever to share your fine-tuned models

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Hugging Face

@huggingface

4 years

Excited to welcome Longformer, the transformer for long-range document tasks, to transformers 🤗(thanks to @i_beltagy ). Try 1 of the 7 models from the model hub: or check out how to convert a pre-trained BERT to its "long" version: .

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Hugging Face

@huggingface

2 years

🎙️ Speech Translation stepped up its game! @MetaAI just released XLS-R, a model pretrained on 128 spoken languages🌍 ... and it's available on the Hub🤗 You can try out the first "All-to-All" Speech Translation checkpoint ever directly on the Hub 🔥 👉

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Hugging Face

@huggingface

3 years

🤗 Transformers v4.9.0: 🟠 Brand new @TensorFlow Examples 🟠: Examples for many NLP tasks are now available using Keras only, thanks to @carrigmat ! 🚀CANINE: Tokenizer-free, character-based model 🚂 Train a tokenizer from another: same config, different dataset!

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Hugging Face

@huggingface

5 years

You can now try “Write with Transformer 🦄”, powered by @OpenAI ’s LARGE GPT-2 model (774 million parameters!), in realtime. Try it out on 🔥 🔥 @jackclarkSF @Miles_Brundage @AlecRad @julien_c @Thom_Wolf @SanhEstPasMoi @ClementDelangue @LysandreJik

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Hugging Face

@huggingface

3 months

We're having some issues on the Hub and looking into them! We should be back soon. Please send hugs🤗

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Hugging Face

@huggingface

2 years

Dataset observability is key to better ML. You can now preview datasets' contents DIRECTLY on the Hub 🔥🎉 Thanks to the streaming feature of datasets, half of the community's datasets are supported out of the box. It also supports Image and Audio datasets, not just text!

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