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The Hugging Face Hub is a platform (centralized web service) for hosting: [19] 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;
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]
The model’s posts and replies also generated a lot of controversy and conflict among the users, who often engaged in heated and violent debates and fights with each other. [8] On Hugging Face, the model’s page received a lot of visits and requests from users who wanted to try out and experiment with the model. The model’s page also ...
The company states that its models are trained to interpret the context in the text, and adjust the intonation and pacing accordingly. [10] It uses advanced algorithms to analyze the contextual aspects of text, aiming to detect emotions like anger, sadness, happiness, or alarm, which enables the system to understand the user's sentiment, [ 11 ...
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Researchers from Hugging Face and Carnegie Mellon University reported in a 2023 paper that generating one thousand 1024×1024 images using Stable Diffusion's XL 1.0 base model requires 11.49 kWh of energy and generates 1,594 grams (56.2 oz) of carbon dioxide, which is roughly equivalent to driving an average gas-powered car a distance of 4.1 ...
It is necessary to collect clean and well-structured raw audio with the transcripted text of the original speech audio sentence. Second, the text-to-speech model must be trained using these data to build a synthetic audio generation model. Specifically, the transcribed text with the target speaker's voice is the input of the generation model.