nlp-recipes
clip-as-service
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nlp-recipes | clip-as-service | |
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5 | 15 | |
6,020 | 12,181 | |
- | 0.6% | |
0.0 | 5.2 | |
over 1 year ago | 3 months ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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nlp-recipes
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Show HN: I turned my microeconomics textbook into a chatbot with GPT-3
https://github.com/topics/automatic-summarization
Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content
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Show HN: DocsGPT, open-source documentation assistant, fully aware of libraries
https://github.com/topics/automatic-summarization
Though now archived,
> Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content
NLP Tasks: Text Classification, Named Entity Recognition, Text Summarization, Entailment, Question Answering, Sentence Similarity, Embeddings, Sentiment Analysis, Model Explainability, and Auto-Annotatiom
- ✨ 5 Free Resources for Learning Natural Language Processing with Python 🚀
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Is there any utility software/bot that produces descriptor tags for a Reddit image post using the comments?
I found this (https://github.com/microsoft/nlp-recipes) resource and it has a list of pre-built or easily customizable NLP models that I'm going to try out.
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Building a Aspect based sentiment classification
There is an NLP recipe from Microsoft on ABSA. Have you seen this? https://github.com/microsoft/nlp-recipes/blob/master/examples/sentiment_analysis/absa/absa.ipynb
clip-as-service
- Search for anything ==> Immich fails to download textual.onnx
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I'm going insane trying to train large datasets for poses, any input would be greatly appreciated I've been stuck for days
I think training models with limited images can lead to overfitting, so I think you can try using a set of images with different poses. You might also want to try flipping or to help out the model so it gets to do different psoes. You might also want CLIP-as-a-service, but just know that pre-trained models isn't always be the best solution. My .02c
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[D]Want to Search Inside Videos Like a Pro?
Imagine an AI-powered grep command, one that could process a film and find segments matching a text. With CLIP-as-service, you can do that. Here is the repo link, https://github.com/jina-ai/clip-as-service.
- Image Similarity Score using transfer learning
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Best models for sentence similarity with good benefit-cost ratio?
you could try Jina.ai's CLIP-as-a-Service: https://github.com/jina-ai/clip-as-service
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Google launched multisearch last week, here's how you can create your own multisearch
Multisearch allows people to search with both text and images. With Open-Source project CLIP-as-service, you can use CLIP (a deep learning model by OpenAI) to do the same. Ask me if you have any questions?
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Natural text to image search(without captions), using CLIP model. Notebook in comment.
Are you scraping these images or using any dataset? Do share the link, would love to play around with it. Would love to hear your feedback for clip-as-service (what I use in my example)?
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Open-Source python package to find relevant images for a sentence
Built CLIP-as-service, an open-source library to create embeddings of images and text using CLIP. These embeddings can be used to find the relevant images for any sentence. Note: you don't need to caption the images for this to work, and it is not just limited to objects in the image but an overall understanding built via CLIP neural network.
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Built an ML library that can describe an image or find relevant images for a sentence
Built [CLIP-as-service](https://github.com/jina-ai/clip-as-service), an open-source library to create embeddings of images and text using CLIP.
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[P] Clip-as-service to embed images and sentences into fixed-length vectors with CLIP
Excited to share my new project CLIP-as-service, a high-scalability service for embedding images and text. It serve CLIP models with ONNX runtime and PyTorch JIT with 800QPS.
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