min-dalle
txtai
min-dalle | txtai | |
---|---|---|
31 | 356 | |
3,474 | 7,033 | |
- | 2.6% | |
0.0 | 9.3 | |
over 1 year ago | 3 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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.
min-dalle
- Open source Python libraries for AI image generation that you can install on an Amazon GPU instance, like min(DALL-E) and Pixray?
- List of open source machine learning AI image generation/text-to-image libraries that can be installed on an Amazon GPU instance? e.g. MinDall-E, Disco Diffusion, Pixray
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Free/open-source AI Text-To-Image Models that can be run on AWS?
min(DALL·E).
- I'm building a timeline for generative image ML models. What's missing?
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DALL·E Now Available in Beta
Additionally, it's also open-sourced on GitHub and can be self-hosted, with easy instructions to do so: https://github.com/kuprel/min-dalle
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dalle update
For CPU, even highly-optimized models like mindalle are prohibitively slow.
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Hii everyone ,Can I build the dalle mini from scratch or not?? Please help!!
Maybe you would be interested in this GitHub repo.
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World of Warcraft Character Beanie Babies
These were generated with DALL-E Mega via min-dalle, which is a more advanced version of DALL-E Mini with better visual fidelity (less blurry) but otherwise similar results.
- Show HN: Generate webpage summary images with DALL-E mini
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"min(DALL·E)" is "a minimal implementation of Boris Dayma's DALL·E Mini in PyTorch. It has been stripped to the bare essentials necessary for doing inference." This uses the DALL-E Mega model. The Google Colab notebook using a Tesla T4 GPU takes 35 seconds to generate 4 images, and 17 seconds for 1.
GitHub repo (contains links to Colab notebook and web app at site Replicate[dot]com). The times mentioned in the title don't included setup time.
txtai
- Show HN: FileKitty – Combine and label text files for LLM prompt contexts
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What contributing to Open-source is, and what it isn't
I tend to agree with this sentiment. Many junior devs and/or those in college want to contribute. Then they feel entitled to merge a PR that they worked hard on often without guidance. I'm all for working with people but projects have standards and not all ideas make sense. In many cases, especially with commercial open source, the project is the base of a companies identity. So it's not just for drive-by ideas to pad a resume or finish a school project.
For those who do want to do this, I'd recommend writing an issue and/or reaching out to the developers to engage in a dialogue. This takes work but it will increase the likelihood of a PR being merged.
Disclaimer: I'm the primary developer of txtai (https://github.com/neuml/txtai), an open-source vector database + RAG framework
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Build knowledge graphs with LLM-driven entity extraction
txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.
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Bootstrap or VC?
Bootstrapping only works if you have the runway to do it and you don't feel the need to grow fast.
With NeuML (https://neuml.com), I've went the bootstrapping route. I've been able to build a fairly successful open source project (txtai 6K stars https://github.com/neuml/txtai) and a revenue positive company. It's a "live within your means" strategy.
VC funding can have a snowball effect where you need more and more. Then you're in the loop of needing funding rounds to survive. The hope is someday you're acquired or start turning a profit.
I would say both have their pros and cons. Not all ideas have the luxury of time.
- txtai: An embeddings database for semantic search, graph networks and RAG
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Ask HN: What happened to startups, why is everything so polished?
I agree that in many cases people are puffing their feathers to try to be something they're not (at least not yet). Some believe in the fake it until you make it mentality.
With NeuML (https://neuml.com), the website is a simple HTML page. On social media, I'm honest about what NeuML is, that I'm in my 40s with a family and not striving to be the next Steve Jobs. I've been able to build a fairly successful open source project (txtai 6K stars https://github.com/neuml/txtai) and a revenue positive company. For me, authenticity and being genuine is most important. I would say that being genuine has been way more of an asset than liability.
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Are we at peak vector database?
I'll add txtai (https://github.com/neuml/txtai) to the list.
There is still plenty of room for innovation in this space. Just need to focus on the right projects that are innovating and not the ones (re)working on problems solved in 2020/2021.
- Txtai: An all-in-one embeddings database for semantic search and LLM workflows
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Generate knowledge with Semantic Graphs and RAG
txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.
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Show HN: Open-source Rule-based PDF parser for RAG
Nice project! I've long used Tika for document parsing given it's maturity and wide number of formats supported. The XHTML output helps with chunking documents for RAG.
Here's a couple examples:
- https://neuml.hashnode.dev/build-rag-pipelines-with-txtai
- https://neuml.hashnode.dev/extract-text-from-documents
Disclaimer: I'm the primary author of txtai (https://github.com/neuml/txtai).
What are some alternatives?
dalle-mini - DALL·E Mini - Generate images from a text prompt
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
dalle-playground - A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini)
tika-python - Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.
CogVideo - Text-to-video generation. The repo for ICLR2023 paper "CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers"
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
imagen-pytorch - Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
faiss - A library for efficient similarity search and clustering of dense vectors.
KoboldAI-Client
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
paperai - 📄 🤖 Semantic search and workflows for medical/scientific papers