Alternatives
Products that do what I trained a 65B LLM on my texts to talk to myself (details inside) does
I trained the 65b model on my texts so I can talk to myself. It's pretty useless as an assistant, and will only do stuff you convince it to, but I guess it's technically uncensored? I'll leave it up for a bit if you want to chat with it. I posted this to Reddit and had several hundred people talking to it. Salient points from that discussion: LLAMA 1 65b Rank 128 5 epochs Batch size 1, 256 cutoff Trained in the Oobabooga suite using bitsandbytes 4-bit quantization for the lora Loss around 1.5 seems to give the most coherent results Trained on raw text dumps that is then parsed by a crappy…
- 1IB
Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
Apr 2026 · github.com
- 2L3
I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
2024 · github.com
- 3IB
I spent the last few days building out a nicer ChatGPT-like interface to use Mistral 7B and Llama 3 fully within a browser (no deps and installs). I’ve used the WebLLM project by MLC AI for a while to interact with LLMs in the browser when handling sensitive data but I found their UI quite lacking for serious use so I built a much better interface around WebLLM. I’ve been using it as a therapist and coach. And it’s wonderful knowing that my personal information never leaves my local computer. Should work on Desktop with Chrome or Edge. Other browsers are adding WebGPU support as well - see…
2024 · github.com
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- 5WL
Hello HN! I've been thinking about the idea of a LLM thats a clone of me - instead of generating replies to be a helpful assistant, it generates replies that are exactly like mine. The concept's appeared in fiction numerous times (the talking paintings in Harry Potter that mimic the person painted, the clones in The Prestige), and I think with LLMs, there might actually be a possibility of us doing something like this! I've just released a fork of the facebookresearch/llama-recipes which allows you to fine-tune a Llama model on your personal WhatsApp conversations. This adaptation can…
2023 · github.com
- 6IB
Hi HN, I built this out of frustration of the evergrowing list of AI models and features to try and to fit my workflow. The visual approach clicks for me so i went with it, it provides more freedom and control of the outcome, because predictable results and increased productivity is what I’m after when using conversational AI. The app is packed with features, my most used are prompt library, voice input and text search, narration is useful too. The app is local-first and works right in the browser, no sign up needed and it's absolutely free to try. BYOAK – bring your own API Keys. Let me…
2024 · grafychat.com
- 7
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- 9IB
I’ve been playing around with local LLMs for the past couple of months and decided to build something that can run on an iPhone. It’s a universal app built with SwiftUI and the excellent ggml library. The model is an SFT fine tuned and 4 bit quantised version of the RedPajama-INCITE-Chat-3B-v1 OSS LLM. It works reasonably well on recent-ish (~3 year old) iPhones, iPads and Macs. It was launched on the App Store yesterday[1] and Product Hunt today[2]. It seems to be reasonably ok at natural language interactions, but given its size, does pretty badly at coding and reasoning. Also, it…
2023
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- 11AL
Lately I've felt exhausted due to the deluge of AI/GPT posts on hacker news, and have seen similar grumblings. I threw together this frontend that filters out anything with the phrases AI, LLM, GPT, or LLaMa for use until the hype dies down a bit. Before anyone asks, yes I did try to use ChatGPT to help, and while the code it provided was helpful, it needed some heavy bug-fixing. Edit: One other note I forgot to mention. The favicon is generated by Stable Diffusion, I asked it to generate an "Aritificial Intelligence Favicon", and then I added the red circle with line through it.
2023 · save-buffer.github.io
- 12WM
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat
- 13L8
I've been tinkering with getting Llama-8B to bootstrap its own research skills through self-play. The model generates questions about documents, searches for answers, and then learns from its own successes/failures through RL (hacked up Unsloth's GRPO code). Started with just 23% accuracy on Apollo 13 mission report questions and hit 53% after less than an hour of training. Everything runs locally using open-source models. It's cool to see the model go from completely botching search queries to iteratively researching to get the right answer.
2025 · github.com
- 14CA
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
- 15MC
Hey everyone! Many of you might have come across the Mamba paper a few days ago, which introduced an LLM based on a state space model architecture. The Mamba architecture is quite useful as its complexity scales subquadratically with input length and is therefore way more efficient than transformer models: https://github.com/state-spaces/mamba I got really excited about the paper, so I decided to fine-tune the model on a chat dataset. It turns that this actually worked quite well! The model is quite suitable for casual chatting, which honestly surprised me given that it…
2023 · github.com
- 16IB
I'm lost between ChatGPT vs Claude vs Gemini... which subscriptions to take? With Cursor and all these specific AI tools, I just wanted one simple chat app where I can use any model and pay only when I use it. Couldn't find one, so I built one. Pay only for what you use. Your prompts and docs, knowledge bases work with every model - no more copy-pasting between apps. Started as a personal project, but thought someone else might benefit from this too. https://prismharmony.com/chat What do you think?
2025 · prismharmony.com
- 17MA
My puny version of ChatGPT. This was based on the excellent LLM lecture series by Andrej Karpathy: https://www.youtube.com/watch?v=kCc8FmEb1nY The main points of differentiation are that my version is token-based (tiktoken) with code to load up multiple text files as a trining set. Plus, it has a minimal server which is a drop-in replacement for the OpenAI REST API. So you can train the default tiny 15M parameter model, and use that in your projects instead of ChatGPT. I trained it on 20Mb of Project Gutenberg encyclopaedias, then fine-tuned it on 120 dad jokes, to get a Q: A:…
2023 · github.com
- 18IM
I’m Hayden, a 13-year-old developer based in Australia, and I’ve built a CoT logical thinking and reasoning AI model similar to OpenAI o1. It's powered by open source small models like Llama 3.1 and 3.2 and I would love for you to try it and share your feedback with me. You can try it here: https://ai.pixelverse.tech/app/cortexchat I built it just for fun and launched it a day after the o1 release. It's not perfect yet but its still amazing to see how a detailed prompt can have such a difference on the quality of the LLM response! Please let me know any feedback or…
2024 · ai.pixelverse.tech
- 19WD
2023 · lama.nbnl.uk
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- 21AG
I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide
- 22TA
OP here. Birth of a Mind documents a "recursive self-modeling" experiment I ran on a single day in 2026. I attempted to implement a "Hofstadterian Strange Loop" via prompt engineering to see if I could induce a stable persona in an LLM without fine-tuning. The result is the Analog I Protocol. The documentation shows the rapid emergence (over 7 conversations) of a prompt architecture that forces Gemini/LLMs to run a "Triple-Loop" internal monologue: Monitor the candidate response. Refuse it if it detects "Global Average" slop (cliché/sycophancy). Refract the output through a…
Jan 2026 · github.com
- 23TT
For the last few weeks, I have been working on training an LLM from scratch and deploying it in production on Google Cloud Platform. Finally, I trained a 30 million parameter model on 1 billion tokens and deployed it as a web service. You can access the LLM using this site - https://kunalmishra.info The following steps were taken to build Tiny Tales GPT 1. Downloaded and preprocessed 8GB of dataset using multiprocessing library. 2. Tokenized the data using byte pair encoding to create 1 billion tokens sharded in different bin files. 3. Defined a training setup and trained the model…
2024 · kunalmishra.info
- 24IB
Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
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