ludwig
clip-as-service
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| ludwig | clip-as-service | |
|---|---|---|
| 3 | 15 | |
| 10,778 | 12,169 | |
| 1.3% | 0.5% | |
| 9.5 | 5.2 | |
| about 4 hours ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
ludwig
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Show HN: Toolkit for LLM Fine-Tuning, Ablating and Testing
This is a great project, little bit similar to https://github.com/ludwig-ai/ludwig, but it includes testing capabilities and ablation.
questions regarding the LLM testing aspect: How extensive is the test coverage for LLM use cases, and what is the current state of this project area? Do you offer any guarantees, or is it considered an open-ended problem?
Would love to see more progress toward this area!
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Python projects with best practices on Github?
Two random examples I found from 30 seconds of googling: Here’s Netflix using it in their crisis management tool, and here’s Uber using it in their deep learning framework.
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Most Frequent 600 Coding Questions on LeetCode
They list themselves all over the internet as an "open source contributor" to Uber, which as far I can tell is based entirely on... reporting that there was an issue with a favicon. To me, it seems like they'll be cheating anybody who employs them based on this, ahem, "experience". And that feels like the tip of the iceberg.
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?
nlp-recipes - Natural Language Processing Best Practices & Examples
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
data-structures-and-algorithms - Resources that I used to crack some big tech & startups interviews
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
DeBERTa - The implementation of DeBERTa
aimet - AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
rclip - AI-Powered Command-Line Photo Search Tool
ai-deadlines - :alarm_clock: AI conference deadline countdowns
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
autonlp - 🤗 AutoNLP: train state-of-the-art natural language processing models and deploy them in a scalable environment automatically
electra - ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators