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The Hugging Face Hub is a platform (centralized web service) for hosting: [20] Git-based code repositories, including discussions and pull requests for projects. models, also with Git-based version control; datasets, mainly in text, images, and audio;
Hugging Face's transformers library can manipulate large language models. [4] Jupyter Notebooks can execute cells of Python code, retaining the context between the execution of cells, which usually facilitates interactive data exploration. [5] Elixir is a high-level functional programming language based on the Erlang VM. Its machine-learning ...
Large collaboration led by Hugging Face: 175 [50] 350 billion tokens (1.6TB) [51] Responsible AI Essentially GPT-3 but trained on a multi-lingual corpus (30% English excluding programming languages) Galactica: November 2022: Meta: 120: 106 billion tokens [52] unknown: CC-BY-NC-4.0 Trained on scientific text and modalities. AlexaTM (Teacher ...
deepset is an enterprise software vendor that provides developers with the tools to build production-ready natural language processing (NLP) systems. It was founded in 2018 in Berlin by Milos Rusic, Malte Pietsch, and Timo Möller. [1] deepset authored and maintains the open source software Haystack [2] and its commercial SaaS offering deepset ...
While OpenAI did not release the fully-trained model or the corpora it was trained on, description of their methods in prior publications (and the free availability of underlying technology) made it possible for GPT-2 to be replicated by others as free software; one such replication, OpenGPT-2, was released in August 2019, in conjunction with a ...
A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot, [15] Uber's Pyro, [16] Hugging Face's Transformers, [17] [18] and Catalyst. [19] [20] PyTorch provides two high-level features: [21] Tensor computing (like NumPy) with strong acceleration via graphics processing units (GPU)
Transformers were first developed as an improvement over previous architectures for machine translation, [4] [5] but have found many applications since. They are used in large-scale natural language processing, computer vision (vision transformers), reinforcement learning, [6] [7] audio, [8] multimodal learning, robotics, [9] and even playing ...
[4] [5] BLOOM is the main outcome of the BigScience collaborative initiative, [ 6 ] a one-year-long research workshop that took place between May 2021 and May 2022. BigScience was led by HuggingFace and involved several hundreds of researchers and engineers from France and abroad representing both the academia and the private sector.