We're constantly looking for ways to make your datasets experience better. What would you like to see next on the Hub? https://
huggingface.co/datasets?task_
categories=task_categories:automatic-speech-recognition&sort=downloads
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@reach_vb
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Hugging Face Hub Seeks User Feedback on Dataset Experience
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Load Dataset to Data Loader in Three Lines Code
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TL;DR: You can go from a loading a dataset to a data loader in just 3 lines of code! https://
gist.github.com/Vaibhavs10/eac
93eee5b9beec6f11db7ee50eb72ea
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New README Updates Simplify Dataset Loading and Processing
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The new READMEs now include:
— Vaibhav (VB) Srivastav (@reach_vb) 13 février 2023
1. Sample snippets to load, process and prepare the datasets
2. Better Dataset tags for discovery
3. Example scripts & leaderboards
All of this to help you get sprinting with ease! 🏃♂️ pic.twitter.com/gterMdG06OThe new READMEs now include:
1. Sample snippets to load, process and prepare the datasets
2. Better Dataset tags for discovery
3. Example scripts & leaderboards All of this to help you get sprinting with ease! -
Audio Datasets Enhanced with Usage Guides on Hugging Face Hub
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Your favourite Audio datasets just got whole of a lot better! 🔥
— Vaibhav (VB) Srivastav (@reach_vb) 13 février 2023
All major audio datasets on the 🤗 Hub will now have a "How to use" page packed with example scripts, to help you get from raw data to a data loader at lightning ⚡️ speed.https://t.co/5Fzkno9DQg pic.twitter.com/RMLplHw0npYour favourite Audio datasets just got whole of a lot better! All major audio datasets on the Hub will now have a "How to use" page packed with example scripts, to help you get from raw data to a data loader at lightning speed. https://
huggingface.co/datasets/mozil
la-foundation/common_voice_11_0
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Google Colab: The Underrated Tool Democratizing Machine Learning
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Not a day goes by where I do not use @GoogleColab
!! I use it for whipping up quick demos, to filing bug reports to sharing code snippets with the community and much more! The impact Colab has had to democratise ML is soooo underrated! -
Open Source Speech Synthesis Models: FastSpeech2, VITS, TorToise
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Yes! My point was referring specific to closed source API the David was mentioning in the video.
All, FastSpeech2, VITS and TorToise (inference) are OSS. :)) -
Open Source AI Alternatives to Paid Closed Source APIs
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My point here was that you can replicate the same with a bit more effort here and there with Open Source alternatives instead of paying a closed source API
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SpeechT5 vs FastSpeech2 vs VITS: TTS Model Comparison
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Ofcourse. It depends on what do you optimise for SpeechT5 TTS (AR) does sound better than vanilla FastSpeech2 (NAR) however worse than VITS/PortaSpeech. Significantly worse than TorToise TTS. However it is considerably slow.
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Open Source AI Models: Flan, OPT-IML, Speech T5 Alternative
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Somebody tell my boi about @huggingface! You can replicate the same more or less (if not better) with Flan/ OPT-IML and Speech T5 TTS on the 🤗hub: https://t.co/fyV1nkC7I0
— Vaibhav (VB) Srivastav (@reach_vb) 10 février 2023
That’s the power of open source ⚡️ https://t.co/0trXRuup01Somebody tell my boi about @huggingface
! You can replicate the same more or less (if not better) with Flan/ OPT-IML and Speech T5 TTS on the hub: https://
huggingface.co/blog/speecht5 That’s the power of open source -
Hugging Face Transformers Bug Report Discussion
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Hi @RasmusToivanen -What kind of bugs did you encounter? Would you mind raising an issue for the same at https://
github.com/huggingface/tr
ansformers/issues
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