Alternatives
Products that do what Retune – the missing frontend for GPT-3 does
Hey everyone! We launched re:tune today to help builders build complex apps on top of GPT-3. With re:tune, you can do things like: - turn any prompt into a chatbot - get API to integrate into your app - create custom fine-tuned models from your (large) dataset - modify your data and tweak parameters to get personalized output. - write a prompt once, and generate variable responses with our variables editor. You can think of this as a supercharged frontend for GPT-3, along with newer langchain techniques. As next step, we are building out features to publish and monetize your LLM apps, feed…
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I've been playing around with https://github.com/zphang/minimal-llama/ and https://github.com/tloen/alpaca-lora/blob/main/finetune.py, and wanted to create a simple UI where you can just paste text, tweak the parameters, and finetune the model quickly using a modern GPU. To prepare the data, simply separate your text with two blank lines. There's an inference tab, so you can test how the tuned model behaves. This is my first foray into the world of LLM finetuning, Python, Torch, Transformers, LoRA, PEFT, and Gradio. Enjoy!
2023 · github.com
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Any Ideas/Suggestions are welcome :)
2024 · mitenmit.github.io
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Hello HN, We built Promptrepo to make finetuning accessible to product teams — not just ML engineers. Last week, OpenAI’s CPO shared how they use fine-tuning for everything from customer support to deep research, and called it the future for serious AI teams. Yet most teams I know still rely on prompting, because fine-tuning is too technical, while the people who have the training data (product managers and domain experts) are often non-technical. With Promptrepo, they can now: - Add training examples in Google Sheets - Click a button to train - Deploy and test instantly - Use OpenAI,…
2025 · promptrepo.com
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Reor is an open-source AI note-taking app that runs models locally. The four main things to know are: 1. Notes are connected automatically with vector search. You can do semantic search + related notes are automatically connected. 2. You can do RAG Q&A on your notes using the local LLM of your choice. 3. Embedding model, LLM, vector db and files are all run or stored locally. 4. Point it to a directory of markdown files (like an Obsidian vault) and it works seamlessly alongside Obsidian. Under the hood, Reor uses Llama.cpp (node-llama-cpp integration), Transformers.js and Lancedb to power…
2024 · github.com
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Hi HN, I built https://rebrain.gg. It's a website which is intended to help you learn new things. I built it for two reasons: 1. To play around with different ways of interacting with a LLM. Instead of a standard chat conversation, the LLM returns question forms the user can directly interact with (and use to continue the conversation with the LLM). 2. Because I thought it would be cool to have a site dedicated to interactive educational content instead of purely consuming content (which I do too much). An example of a (useful-for-me) interactive conversation is:…
Feb 2026
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Hey Hacker News! Launching gptengineer.app into beta today. It's like Claude Artifacts, but: - you can edit the code in your fav IDE (two-way github sync) - installs npm packages - automatically picks up build and runtime errors and fixes them - very fast, built with rust The full stack capabilities are built on supabase (prefer to not have to handle auth + user data at this point so this is owned by the user) The seed for this project was an open source experiment, posted about that previously here: https://news.ycombinator.com/item?id=36422730 Would love feedback if you give…
2024 · gptengineer.app
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Built a tool for transforming unstructured data into structured outputs using language models (with 100% adherence). If you're facing problems getting GPT to adhere to a schema (JSON, XML, etc.) or regex, need to bulk process some unstructured data, or generate synthetic data, check it out. We run our own tuned model (you can self-host if you want), so, we're able to have incredibly fine grained control over text generation. Repository: https://github.com/automorphic-ai/trex Playground: https://automorphic.ai/playground
2023 · automorphic.ai
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2022 · github.com
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Using threaded emscripten to speed up the generation and offload the main loop. No SIMD or other optimizations. Might work faster with #enable-experimental-webassembly-features enabled. Tested in x86 Chrome and Firefox, Apple Silicon Safari Run it yourself: https://github.com/lxe/ggml/tree/wasm-demo Thanks, https://github.com/ggerganov/ggml,
2023 · lxe.co
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Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available. I've found it particularly useful for - Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly - Understanding different tokenization patterns and how it affects model output - Getting a general sense of how "hard" different prediction tasks are for GPT-style models Known problems (that I probably…
2023 · perplexity.vercel.app
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It works on top of the open-source workflow engine windmill [1] that you can easily self-host on a tiny server or a large k8s cluster. You will also need pgvector (here hosted on supabase) and of course a GPT4 api key. It showcases an approval step so that you only provide answers you are confident giving to your users, which feels less robotic. All the building blocks are scripts that you can reuse outside of windmill and you could build this in any other workflow engines (although less conveniently). We use it for our own needs on discord [2] and thoughts this was a common need for any…
2023 · windmill.dev
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Hey folks, we created a ChatGPT alternative for anyone to try out LLaMA models and benchmark responses across OpenAI's models and other open source models. Would love some feedback! No data is being used for retraining models.
2023 · chat.nbox.ai
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