Alternatives
Products that do what Fine-tuned Llama 3.2 3B to match 70B models for local transcripts does
I wrote a small local tool to transcribe audio notes (Whisper/Parakeet). Code: https://github.com/bilawalriaz/lazy-notes I wanted to process raw transcripts locally without OpenRouter. Llama 3.2 3B with a prompt was decent but incomplete, so I tried SFT. I fine-tuned Llama 3.2 3B to clean/analyze dictation and emit structured JSON (title, tags, entities, dates, actions). Data: 13 real memos → Kimi K2 gold JSON → ~40k synthetic + gold; keys canonicalized. Chutes.ai (5k req/day). Training: RTX 4090 24GB, ~4h, LoRA (r=128, α=128, dropout=0.05), max seq 2048,…
- 1FL
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
- 2IB
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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- 4WO
Hey HN! Braden here, creator of Whispering, an open-source speech-to-text app. I really like dictation. For years, I relied on transcription tools that were almost good, but they were all closed-source. Even a lot of them that claimed to be “local” or “on-device” were still black boxes that left me wondering where my audio really went. So I built Whispering. It’s open-source, local-first, and most importantly, transparent with your data. Your data is stored locally on your device, and your audio goes directly from your machine to a local provider (Whisper C++, Speaches, etc.) or your chosen…
2025 · github.com
- 5LD
2023 · github.com
- 6L3
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
- 7SH
Schibsted created a transcription service for our journalists to transcribe audio interviews and podcasts really quick.
2023 · github.com
- 88F
Hi HN! I'm just sharing a project I've been working on during the LLM Efficiency Challenge - you can now finetune Llama with QLoRA 5x faster than Huggingface's original implementation on your own local GPU. Some highlights: 1. Manual autograd engine - hand derived backprop steps. 2. QLoRA / LoRA 80% faster, 50% less memory. 3. All kernels written in OpenAI's Triton language. 4. 0% loss in accuracy - no approximation methods - all exact. 5. No change of hardware necessary. Supports NVIDIA GPUs since 2018+. CUDA 7.5+. 6. Flash Attention support via Xformers. 7. Supports 4bit and 16bit…
2023 · github.com
- 9NI
This lets you talk to local LLMs in Apple Notes. I saw Obsidian Ollama (https://github.com/hinterdupfinger/obsidian-ollama) and thought it was handy, but I'm too lazy to migrate away from the Apple ecosystem, so I quickly hacked this together. I tend to use Notes as a scratchpad for prompts, so it's nice to do some quick inference without leaving the app. Notes doesn't really support plugins so I'm using the macOS accessibility API for reading selections and then stream responses using the clipboard (not ideal but it works).
2024 · smallest.app
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- 12BC
I know there are various tools that are supposed to make this easy, but I couldn't find anything that did everything I wanted, so I made this today for fun. The web-based offerings all take forever and seem flaky, and you need to process one video at a time, with no control over the transcription settings. In contrast, my script lets you convert a whole playlist in bulk with full control over everything. It's truly easy to use-- you can clone the repo, install to a venv, and be generating a folder full of high quality transcript text files in under 5 minutes. All you need to do is supply the…
2023 · github.com
- 13G4
About six months ago, I started working on a project to fine-tune Whisper locally on my M2 Ultra Mac Studio with a limited compute budget. I got into it. The problem I had at the time was I had 15,000 hours of audio data in Google Cloud Storage, and there was no way I could fit all the audio onto my local machine, so I built a system to stream data from my GCS to my machine during training. Gemma 3n came out, so I added that. Kinda went nuts, tbh. Then I put it on the shelf. When Gemma 4 came out a few days ago, I dusted it off, cleaned it up, broke out the Gemma part from the Whisper…
Apr 2026 · github.com
- 14IM
A few years ago, right after high school, I decided to try to make a simultaneous translation app for Android as a side project, it took longer than expected (about 2 years) and I had to make a lot of compromises (I had to use Google's API and therefore make users use a developer key because at the time there were no free solutions for speech recognition and translation that had good quality). At the end of university, I decided to pick it up again and finally, using OpenAi's Whisper for speech recognition and Meta's NLLB for translation (with both running locally on the phone), I managed to…
2024 · github.com
- 15FL
2024 · colab.research.google.com
- 16
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- 18PS
Welcome to Project S.A.T.U.R.D.A.Y. This is a project that allows anyone to easily build their own self-hosted J.A.R.V.I.S-like voice assistant. In my mind vocal computing is the future of human-computer interaction and by open sourcing this code I hope to expedite us on that path. I have had a blast working on this so far and I'm excited to continue to build with it. It uses whisper.cpp [1], Coqui TTS [2] and OpenAI [3] to do speech-to-text, text-to-text and text-to-speech inference all 100% locally (except for text-to-text). In the future I plan to swap out OpenAI for llama.cpp [4]. It is…
2023 · github.com
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- 20RP
Hey hacker news, We’re the cofounders at Psychic.dev (http://psychic.dev) where we help companies connect LLMs to private data. With the launch of Llama 2, we think it’s finally viable to self-host an internal application that’s on-par with ChatGPT, so we did exactly that and made it an open source project. We also included a vector DB and API server so you can upload files and connect Llama 2 to your own data. The RAG in RAGstack stands for Retrieval Augmented Generation, a technique where the capabilities of a large language model (LLM) are augmented by retrieving information…
2023 · github.com
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- 22LL
What it is A single 45 MB Windows .exe that embeds llama.cpp and a minimal Tk UI. Copy it (plus any .gguf model) to a flash drive, double-click on any Windows PC, and you’re chatting with an LLM—no admin rights, Cloud, or network. Why I built it Existing “local LLM” GUIs assume you can pip install, pass long CLI flags, or download GBs of extras. I wanted something my less-technical colleagues could run during a client visit by literally plugging in a USB drive. How it works PyInstaller one-file build → bundles Python runtime, llama_cpp_python, and the UI into a single PE. On first launch, it…
2025 · github.com
- 23AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com
- 24IB
I originally added this to my site to speed up my video editing process. Last year I started a youtube channel and for some of my longer videos it's annoying to rely on youtube or capcut to transcribe when Whisper is open source. Capcut also recently updated their T&Cs to say they own your content if you use their app, so I cancelled my subscription. Another use-case I have is recording my claude prompts as audio, transcribing them, and then pasting them into my terminal. I mostly work on the CLI (claude, ffmpeg, whisper), but I wanted to make a browser version. Not reinventing the wheel…
2025 · meetcosmos.com
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