clip-as-service
ABSA-PyTorch
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| clip-as-service | ABSA-PyTorch | |
|---|---|---|
| 15 | 1 | |
| 12,193 | 1,945 | |
| 0.7% | - | |
| 5.2 | 0.0 | |
| 3 months ago | 11 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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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.
ABSA-PyTorch
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Is there an open-source way to replicate entity-level sentiment from Google's Cloud Natural Language API?
I'm learning about NLP and was really impressed with Google's Natural Language API (demo). It seems that entity-level sentiment analysis is the future of NLP. Has anyone in the community come across open-source libraries that replicate the API (although of course with lower F1 scores). I found an excellent repo called ABSA-PyTorch but it seems that all the implementations are classification-based; that is, they return "positive/negative" rather than a spectrum between positive and negative. Is there a sub field of Aspect-Based Sentiment Analysis (ABSA) that isn't classification based? I wasn't able to find any keywords despite hours of Google searching.
What are some alternatives?
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
nlphose - Enables creation of complex NLP pipelines in seconds, for processing static files or streaming text, using a set of simple command line tools. Perform multiple operation on text like NER, Sentiment Analysis, Chunking, Language Identification, Q&A, 0-shot Classification and more by executing a single command in the terminal. Can be used as a low code or no code Natural Language Processing solution. Also works with Kubernetes and PySpark !
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
entity-sentiment-analysis - Various ops for handling several entities in a document, perform anaphora resolution, clustering, etc.
DeBERTa - The implementation of DeBERTa
ERNIE - Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
rclip - AI-Powered Command-Line Photo Search Tool
obsei - Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
electra - ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
ARElight - Granular Viewer of Sentiments Between Entities in Massively Large Documents and Collections of Texts, powered by AREkit