Étiquette : Hugging Face

https://aws.amazon.com/fr/blogs/machine-learning/improve-high-value-research-with-hugging-face-and-amazon-sagemaker-asynchronous-inference-endpoints/

Hugging Face is the home for all Machine Learning tasks. Here you can find what you need to get started with a task: demos, use cases, models, datasets, and more! https://huggingface.co/tasks

https://www.philschmid.de/huggingface-transformers-keras-tf

https://codistro.medium.com/fine-tuning-bert-for-tweets-classification-ft-hugging-face-8afebadd5dbf

https://www.philschmid.de/serverless-transformers-sagemaker-huggingface New Serverless Transformers using Amazon SageMaker Serverless Inference and Hugging Face Amazon SageMaker Serverless Inference. Amazon SageMaker Serverless Inference is a fully managed serverless inference option that makes it easy for you to deploy and scale ML models built on top of AWS Lambda and fully integrated into the Amazon SageMaker service. Serverless Inference…

https://www.philschmid.de/huggingface-transformers-keras-tf

https://huggingface.co/spaces/Hellisotherpeople/Interpretable_Text_Classification_And_Clustering

https://huggingface.co/d4data/bias-detection-model

https://huggingface.co/hardware Optimum: the ML Hardware Optimization Toolkit for Production We’re on a journey to advance and democratize artificial intelligence through open source and open science. huggingface.co

https://huggingface.co/blog/few-shot-learning-gpt-neo-and-inference-api

https://huggingface.co/blog/sagemaker-distributed-training-seq2seq Distributed Training: Train BART/T5 for Summarization using 🤗 Transformers and Amazon SageMaker Tutorial We will use the new Hugging Face DLCs and Amazon SageMaker extension to train a distributed Seq2Seq-transformer model on the summarization task using the transformers and datasets libraries, and then upload the model to huggingface.co and test it.. As distributed training…

Summer of Language Models 21 https://bigscience.huggingface.co/en/#!index.md

https://huggingface.co/blog/bert-cpu-scaling-part-1

https://www.comet.ml/site/comet-hugging-face-integration/ Comet ❤️ Hugging Face 🤗 Get started with auto-logging model metrics and parameters to Comet from the Hugging Face transformers library. www.comet.ml

https://www.kaggle.com/funtowiczmo/hugging-face-transformers-get-started Hugging Face Transformers – Get started ! | Kaggle We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. www.kaggle.com

https://m.youtube.com/watch?v=t86G11tfVNw

https://github.com/deepset-ai/haystack/

https://github.com/huggingface/datasets

https://github.com/huggingface/pytorch_block_sparse

https://medium.com/swlh/bert-step-by-step-b7ff47fcfbe

https://github.com/huggingface/nlp

https://app.wandb.ai/jxmorris12/huggingface-demo/reports/A-Step-by-Step-Guide-to-Tracking-Hugging-Face-Model-Performance–VmlldzoxMDE2MTU

https://towardsdatascience.com/working-with-hugging-face-transformers-and-tf-2-0-89bf35e3555a

https://www.youtube.com/watch?v=WiHvs1PmZ_4&feature=youtu.be

https://github.com/huggingface/awesome-papers

https://venturebeat.com/2019/09/26/hugging-face-launches-popular-transformers-nlp-library-for-tensorflow/