content.raw: I have put together a notebook on Multimodal RAG, where we do not process the documents with hefty pipelines but natively use:
content.type: text
content.value: I have put together a notebook on Multimodal RAG, where we do not process the documents with hefty pipelines but natively use:
content.type: new_line
content.raw: - 
content.type: text
content.value: - 
content.raw: https://huggingface.co/vidore/colpali
content.id: vidore/colpali
content.type: model
content.type: resource
content.url: https://huggingface.co/vidore/colpali
content.raw:  for retrieval 📖 it doesn't need indexing with image-text pairs but just images!
content.type: text
content.value:  for retrieval 📖 it doesn't need indexing with image-text pairs but just images!
content.type: new_line
content.raw: - 
content.type: text
content.value: - 
content.raw: https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct
content.id: Qwen/Qwen2-VL-2B-Instruct
content.type: model
content.type: resource
content.url: https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct
content.raw:  for generation 💬 directly feed images as is to a vision language model with no processing to text! 
content.type: text
content.value:  for generation 💬 directly feed images as is to a vision language model with no processing to text! 
content.type: new_line
content.raw: I used ColPali implementation of the new 🐭 Byaldi library by 
content.type: text
content.value: I used ColPali implementation of the new 🐭 Byaldi library by 
content.raw: @bclavie
content.type: mention
content.user: bclavie
content.raw:   🤗
content.type: text
content.value:   🤗
content.type: new_line
content.href: https://github.com/answerdotai/byaldi
content.raw: https://github.com/answerdotai/byaldi
content.type: link
content.type: new_line
content.raw: Link to notebook: 
content.type: text
content.value: Link to notebook: 
content.href: https://github.com/merveenoyan/smol-vision/blob/main/ColPali_%2B_Qwen2_VL.ipynb
content.raw: https://github.com/merveenoyan/smol-vision/blob/main/ColPali_%2B_Qwen2_VL.ipynb
content.type: link
content.type: new_line
rawContent: I have put together a notebook on Multimodal RAG, where we do not process the documents with hefty pipelines but natively use:
  - https://huggingface.co/vidore/colpali for retrieval 📖 it doesn't need indexing with image-text pairs but just images!
  - https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct for generation 💬 directly feed images as is to a vision language model with no processing to text! 
  I used ColPali implementation of the new 🐭 Byaldi library by @bclavie  🤗
  https://github.com/answerdotai/byaldi
  Link to notebook: https://github.com/merveenoyan/smol-vision/blob/main/ColPali_%2B_Qwen2_VL.ipynb
  
reactions.reaction: 🔥
reactions.users: rwightman umair894 clem louisbrulenaudet s3nh John6666 BasitMustafa Johnyquest7 phanhoang resbyte denizaybey allandclive fdaudens vilarin ak0601 rreed-pha xi0v Rajaram1996 Rayvee oceansweep parjun byteprobe Filippo
reactions.reaction: 👍
reactions.users: hitchhiker3010 Csplk sasikiran fsommers rogermt navin7 sambarnett96 oceansweep ysdede shreyamondal
reactions.reaction: ❤️
reactions.users: rreed-pha oceansweep Yassmen madstuntman11