TEXTOIR
TEXTOIR is the first opensource toolkit for text open intent recognition. (ACL 2021) (by thuiar)
clip-as-service
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP (by jina-ai)
| TEXTOIR | clip-as-service | |
|---|---|---|
| 1 | 15 | |
| 179 | 12,193 | |
| 4.5% | 0.3% | |
| 7.7 | 5.2 | |
| 3 months ago | 3 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TEXTOIR
Posts with mentions or reviews of TEXTOIR.
We have used some of these posts to build our list of alternatives
and similar projects.
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[D] Extracting next action from conversation
- Intent extraction models such as https://github.com/thuiar/textoir. My problem with this approach is that they are multi-label classifiers and usually focused on single-sentence classification "Can you get me a table?" would be assigned to the "Reservation" label. I feel that I would lose information such as "Meet at 10PM in this address."
clip-as-service
Posts with mentions or reviews of clip-as-service.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-31.
- 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?
When comparing TEXTOIR and clip-as-service you can also consider the following projects:
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
DeBERTa - The implementation of DeBERTa
rclip - AI-Powered Command-Line Photo Search Tool
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
electra - ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
OpenPrompt - An Open-Source Framework for Prompt-Learning.
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
scibert - A BERT model for scientific text.
tensorflow-open_nsfw - Tensorflow Implementation of Yahoo's Open NSFW Model
jina - ☁️ Build multimodal AI applications with cloud-native stack
TEXTOIR vs transformers
clip-as-service vs BERTopic
clip-as-service vs transformers
clip-as-service vs DeBERTa
clip-as-service vs rclip
clip-as-service vs spaCy
clip-as-service vs electra
clip-as-service vs OpenPrompt
clip-as-service vs ludwig
clip-as-service vs scibert
clip-as-service vs tensorflow-open_nsfw
clip-as-service vs jina