Multimodal Embedding #14
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[Title] Multimodal Embedding [Version] initial [Language] ENG [Package] langchain-experimental,pillow,open_clip_torch,scikit-learn,numpy,requests Langchain and Multimodal Embedding Tutorial - Serving the `OpenCLIP` Embedding model using `huggingface` and `langchain-experimental`. - In this example, we obtain `cosine similarity` between **'image(query)-image'** or **'text(query)-image'**, and based on this, we search the dataset for Top5 images most similar to the query.
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현재 배정된 1명 reviewer github ID를 몰라서 못 넣고있음... 확인시 추가 예정 |
[Title] Multimodal Embedding [Version] hotfix [Language] ENG [Package] langchain-experimental,pillow,open_clip_torch,scikit-learn,numpy,requests Langchain and Multimodal Embedding Tutorial - Serving the `OpenCLIP` Embedding model using `huggingface` and `langchain-experimental`. - In this example, we obtain `cosine similarity` between **'image(query)-image'** or **'text(query)-image'**, and based on this, we search the dataset for Top5 images most similar to the query. Hotfix - 2024.12.30 - `Setting Image Data` section markdown change - `./data/for_embed_images` -> `./data/for_embed_images`
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hotfix commit message
커밋 메시지 실수 했네요 ㅠㅠ |
teddylee777
approved these changes
Dec 30, 2024
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제가 하고있는 쪽이 비전쪽 멀티모달 쪽을 하고 있어서 단순 LLM보다는 이쪽이 좀 더 익숙하긴 하네요..ㅎ AI 트랜드가 멀티모달쪽으로 발전해 나아가니까 우리 튜토리얼도 이런 부분이 추가되면 좋을것 같아서 추가 했습니다! 🤗 |
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@pupba 정말 감사합니다. 멀티모달 쪽의 앞으로 신규 콘텐츠쪽도 기대 많이 하겠습니다! |
krkrong
approved these changes
Dec 31, 2024
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[Review]
- Review OS : MAC
- Template Rule 가이드를 준수 하였는가? : YES
- Table of Contents 의 링크가 원활하게 동작하는지 확인하였는가? : YES
- 이미지가 포함되어 있다면, 이미지의 파일명이 가이드를 준수하였는가? : YES
- import 구문이 예전 legacy 방식이 아닌 최신 버전을 따르는가? : YES
- 모든 코드가 동작에 오류 없이 동작하는가? : YES
- 기타 의견:
정말 양질의 콘텐츠이네요!
검수하면서 저도 큰 배움 얻어갑니다. 고생 많으셨습니다!
새해 복 많이 받으세요 :)
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@krkrong 감사합니다 고생하셨어요 :) |
eunhhyy
pushed a commit
to eunhhyy/LangChain-OpenTutorial
that referenced
this pull request
Jan 1, 2025
Multimodal Embedding
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[Title] Multimodal Embedding
[Version] initial
[Language] ENG
[Package] langchain-experimental,pillow,open_clip_torch,scikit-learn,numpy,requests
Langchain and Multimodal Embedding Tutorial
OpenCLIPEmbedding model usinghuggingfaceandlangchain-experimental.cosine similaritybetween 'image(query)-image' or 'text(query)-image', and based on this, we search the dataset for Top5 images most similar to the query.