scibert
clip-as-service
| scibert | clip-as-service | |
|---|---|---|
| 2 | 15 | |
| 1,402 | 12,193 | |
| 0.0% | 0.3% | |
| 0.0 | 5.2 | |
| about 2 years ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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scibert
- Galactica: an AI trained on humanity's scientific knowledge
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Looking for an automatic text summarization method for academic papers
Hey if you are building Seq2Seq models to summarize papers and already have the dataset you can look into using SciBert by allenai and u might have a look at S2ORC as ur dataset. Its quite vast and expansive.
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.
What are some alternatives?
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
paperai - 📄 🤖 Semantic search and workflows for medical/scientific papers
DeBERTa - The implementation of DeBERTa
BERT-pytorch - Google AI 2018 BERT pytorch implementation
rclip - AI-Powered Command-Line Photo Search Tool
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
galai - Model API for GALACTICA
electra - ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators