Bertrand Chevrier's picture

Bertrand Chevrier

kramp

AI & ML interests

text 2 speech, ai for music writting

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upvoted an article 3 days ago
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MiniMax-01 is Now Open-Source: Scaling Lightning Attention for the AI Agent Era

By MiniMax-AI β€’
β€’ 32
reacted to Xenova's post with πŸ”₯ 16 days ago
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First project of 2025: Vision Transformer Explorer

I built a web app to interactively explore the self-attention maps produced by ViTs. This explains what the model is focusing on when making predictions, and provides insights into its inner workings! 🀯

Try it out yourself! πŸ‘‡
webml-community/attention-visualization

Source code: https://github.com/huggingface/transformers.js-examples/tree/main/attention-visualization
liked a Space 16 days ago
reacted to YannisTevissen's post with πŸ‘ 19 days ago
reacted to FranckAbgrall's post with πŸ‘ about 1 month ago
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2003
Hey!

✨ If you're using HF access tokens, we just released an overview of the permissions for fine-grained tokens by hovering over the badge on token settings page (org and user)

It will show the highest permission you've set for each entity πŸ‘€
reacted to julien-c's post with πŸ”₯ about 1 month ago
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8421
After some heated discussion πŸ”₯, we clarify our intent re. storage limits on the Hub

TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)

docs: https://huggingface.co/docs/hub/storage-limits

We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community πŸ”₯

cc: @reach-vb @pierric @victor and the HF team
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upvoted an article about 2 months ago
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Use Models from the Hugging Face Hub in LM Studio

By yagilb β€’
β€’ 132
reacted to cfahlgren1's post with ❀️ about 2 months ago
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You can clean and format datasets entirely in the browser with a few lines of SQL.

In this post, I replicate the process @mlabonne used to clean the new microsoft/orca-agentinstruct-1M-v1 dataset.

The cleaning process consists of:
- Joining the separate splits together / add split column
- Converting string messages into list of structs
- Removing empty system prompts

https://huggingface.co/blog/cfahlgren1/the-beginners-guide-to-cleaning-a-dataset

Here's his new cleaned dataset: mlabonne/orca-agentinstruct-1M-v1-cleaned
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