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This is shown to be great at document retrieval and everyone should test it out in their RAG setups."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"link","href":"https://huggingface.co/posts/merve/663466156074132","raw":"https://huggingface.co/posts/merve/663466156074132"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"In an effort to build a FLUX level open source image generation model, the community is building a dataset of image preferences. The dataset is already open and the project is still running. Join in! ","raw":"In an effort to build a FLUX level open source image generation model, the community is building a dataset of image preferences. The dataset is already open and the project is still running. Join in! 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54 26 11

ben burtenshaw

burtenshaw

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Reacted to their post with ❤️ 2 days ago

For anyone looking to boost their LLM fine-tuning and alignment skills this decemeber. We're running this free and open course called smol course. It’s not big like Li Yin and @mlabonne, it’s just smol. 👷 It focuses on practical use cases, so if you’re working on something, bring it along. 👯‍♀️ It’s peer reviewed and open so you can discuss and get feedback. 🤘 If you’re already a smol pro, feel free to drop a star or issue. > > Part 1 starts now, and it’s on instruction tuning! https://github.com/huggingface/smol-course

posted an update 2 days ago

upvoted an article 5 days ago

Use Models from the Hugging Face Hub in LM Studio

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Articles

Argilla 2.4: Easily Build Fine-Tuning and Evaluation datasets on the Hub — No Code Required

Nov 4

• 41

How to build a custom text classifier without days of human labeling

Oct 17

• 55

How to optimize your data labelling project with custom interfaces

Oct 16

• 18

⚗️ 🔥 Building High-Quality Datasets with distilabel and Prometheus 2

Jun 3

• 26

⚗️ 🧑🏼‍🌾 Let's grow some Domain Specific Datasets together

Apr 29

• 29

Organizations

Posts 3

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1646

For anyone looking to boost their LLM fine-tuning and alignment skills this decemeber. We're running this free and open course called smol course. It’s not big like Li Yin and @mlabonne , it’s just smol.

👷 It focuses on practical use cases, so if you’re working on something, bring it along.

👯‍♀️ It’s peer reviewed and open so you can discuss and get feedback.

🤘 If you’re already a smol pro, feel free to drop a star or issue.

> > Part 1 starts now, and it’s on instruction tuning!

https://github.com/huggingface/smol-course

Post

1544

[SATURDAY ROUNDUP] ☕️🧑‍🎓

In case you missed everything this week. It’s all about vision language models and image preference datasets. Here are the models and datasets you can use in your projects.

QWQ-32B-Preview is the first open weights model to reason like o1 with comparable performance. It’s large but is acing some of the hardest tasks.

https://bsky.app/profile/philschmid.bsky.social/post/3lbylz6nzqk25

SmolVLM is a vision implementation of the recently released SmolLM2. It uses the Idefics3 approach to add a vision encoder. The main difference being the smaller language model (8b > 1.7b) and more compression of images. This results in a model that is very accurate for its memory footprint.

https://huggingface.co/blog/smolvlm

ColSmolVLM is a vision embedding model based on SmolVLM using the Colbert approach from ColPali. This is shown to be great at document retrieval and everyone should test it out in their RAG setups.

https://huggingface.co/posts/merve/663466156074132

In an effort to build a FLUX level open source image generation model, the community is building a dataset of image preferences. The dataset is already open and the project is still running. Join in!

https://huggingface.co/posts/davidberenstein1957/405018978675827

TRL tutorial Drop - This week I dropped a load of tutorials on finetuning and aligning models with TRL. If you’re upskilling in this space, you should check these out.

https://bsky.app/profile/benburtenshaw.bsky.social/post/3lbrc56ap3222

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