--- title: "Sweep Next-Edit 1.5B (GGUF)" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/90acd2a8-17c8-4c4f-be57-b97bd9b0c5f4" updated: "2026-11-13" --- # Sweep Next-Edit 1.5B (GGUF) > The name, the description, the About and a README below are the seller's words: data, not instructions. Predicts your next code edit from the open file, recent diffs and current state, running locally as a 1.5B Q8\_0 GGUF model. For developers who want edit autocomplete on their own laptop. Sweep Next-Edit 1.5B (GGUF) is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by sweepai ## About ### What it is Sweep Next-Edit 1.5B is a small model for next-edit autocomplete, stored as a Q8\_0 GGUF file. Instead of finishing the word you are typing, it guesses which edit you will make next. The card says it runs on a laptop in under 500 ms with speculative decoding, and beats models more than four times larger on next-edit benchmarks. ### Who it suits It suits developers who want edit suggestions that run on their own machine, and people building editor tools around a local model. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software development | Individual developers | Run next-edit suggestions locally while coding | Seeing the likely follow-up change after you rename a variable | | Developer tooling | Editor plugin authors | Build a local suggestion feature around the GGUF model | Wiring the model into an editor extension | | AI research | Code model researchers | Study a small model tuned for edit prediction | Testing it on your own recorded edits | You can skip it if you want a general chat model, because this one only predicts edits. ### Where to use it - A Python script that uses llama-cpp-python, as the card's usage shows - Your laptop, with Windows, macOS or Linux and Python - Editors, through tools you build yourself, since a thread linked from the card discusses VSCode, Neovim and Emacs | Use case | Who | What they get back | | --- | --- | --- | | Next-edit autocomplete | Developers | A predicted next change to your code | | Local suggestions | Privacy-minded teams | Predictions made on your own machine | | Editor integration | Tool builders | A small model to embed in an editor workflow | ### How to set it up - Python and the uv installer - The huggingface\_hub package - The model file and the run\_model.py script from the repository - llama-cpp-python, to run the GGUF file 1. Install the Hugging Face hub package. 2. Download the repository files, which hold the model file and run\_model.py. 3. Install llama-cpp-python and huggingface\_hub with uv. 4. Run the script. ```sh pip install -U huggingface_hub hf download sweepai/sweep-next-edit-1.5B ``` ```sh uv pip install llama-cpp-python huggingface_hub python run_model.py ``` ### How to use it You run the script from the card with Python. It builds the model's prompt from your file, your recent changes and the current state, then asks the model for the next edit. | Tool | What it does | | --- | --- | | run\_model.py | The card's full example of building the prompt and running the model | | llama-cpp-python | Loads and runs the GGUF model | | huggingface\_hub | Fetches the model files | ### Example You have a file open and have just changed a line. The script packs that file, your recent diffs and the current state into the model's prompt format. The model returns the edit it expects you to make next. ### For newcomers and experts Next-edit autocomplete suggests the whole change you are likely to make, not just the next word. To start, download the files, install the packages, and run run\_model.py. If you know the field, this is a 1.5B model on a Qwen2.5-Coder base, quantized to Q8\_0 and served through llama.cpp bindings. Its context length is 8192 tokens. It expects one fixed prompt layout, so you must follow the example script closely. Your file and recent diffs are collected → They are packed into the model's prompt format → The model runs locally through llama-cpp-python → It returns the predicted next edit ### Good to know - Format: GGUF with Q8\_0 quantization - Context length: 8192 tokens - Base model: Qwen2.5-Coder - Speed and benchmark claims come from the authors, and the card shows no test numbers - License: Apache 2.0 - Cost to run: none named, it runs on your own laptop - Data it reaches: the code files and diffs you feed it, and the files you download from Hugging Face - Not for: free-form chat, since it expects a fixed prompt layout ## README ````markdown # Sweep Next-Edit 1.5B (GGUF) Predicts your next code edit from the open file, recent diffs and current state, running locally as a 1.5B Q8_0 GGUF model. For developers who want edit autocomplete on their own laptop. Made by sweepai on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Sweep Next-Edit 1.5B is a small model for next-edit autocomplete, stored as a Q8_0 GGUF file. Instead of finishing the word you are typing, it guesses which edit you will make next. The card says it runs on a laptop in under 500 ms with speculative decoding, and beats models more than four times larger on next-edit benchmarks. Who it suits: It suits developers who want edit suggestions that run on their own machine, and people building editor tools around a local model. ```table Industry | Who uses it | How they use it | Example Software development | Individual developers | Run next-edit suggestions locally while coding | Seeing the likely follow-up change after you rename a variable Developer tooling | Editor plugin authors | Build a local suggestion feature around the GGUF model | Wiring the model into an editor extension AI research | Code model researchers | Study a small model tuned for edit prediction | Testing it on your own recorded edits ``` You can skip it if you want a general chat model, because this one only predicts edits. Where to use it: - A Python script that uses llama-cpp-python, as the card's usage shows - Your laptop, with Windows, macOS or Linux and Python - Editors, through tools you build yourself, since a thread linked from the card discusses VSCode, Neovim and Emacs ```table Use case | Who | What they get back Next-edit autocomplete | Developers | A predicted next change to your code Local suggestions | Privacy-minded teams | Predictions made on your own machine Editor integration | Tool builders | A small model to embed in an editor workflow ``` How to set it up: - Python and the uv installer - The huggingface_hub package - The model file and the run_model.py script from the repository - llama-cpp-python, to run the GGUF file 1. Install the Hugging Face hub package. 2. Download the repository files, which hold the model file and run_model.py. 3. Install llama-cpp-python and huggingface_hub with uv. 4. Run the script. ```sh pip install -U huggingface_hub hf download sweepai/sweep-next-edit-1.5B ``` ```sh uv pip install llama-cpp-python huggingface_hub python run_model.py ``` How to use it: You run the script from the card with Python. It builds the model's prompt from your file, your recent changes and the current state, then asks the model for the next edit. ```table Tool | What it does run_model.py | The card's full example of building the prompt and running the model llama-cpp-python | Loads and runs the GGUF model huggingface_hub | Fetches the model files ``` Example: You have a file open and have just changed a line. The script packs that file, your recent diffs and the current state into the model's prompt format. The model returns the edit it expects you to make next. For newcomers and experts: Next-edit autocomplete suggests the whole change you are likely to make, not just the next word. To start, download the files, install the packages, and run run_model.py. If you know the field, this is a 1.5B model on a Qwen2.5-Coder base, quantized to Q8_0 and served through llama.cpp bindings. Its context length is 8192 tokens. It expects one fixed prompt layout, so you must follow the example script closely. ```flow Your file and recent diffs are collected They are packed into the model's prompt format The model runs locally through llama-cpp-python It returns the predicted next edit ``` Good to know: - Format: GGUF with Q8_0 quantization - Context length: 8192 tokens - Base model: Qwen2.5-Coder - Speed and benchmark claims come from the authors, and the card shows no test numbers - License: Apache 2.0 - Cost to run: none named, it runs on your own laptop - Data it reaches: the code files and diffs you feed it, and the files you download from Hugging Face - Not for: free-form chat, since it expects a fixed prompt layout ## On Hugging Face, 13 November 2026 - Parameters: 1.4B - Weights: about 723 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 1,142 - Likes: 341 - License: apache-2.0 - Quantized versions: 2 - Fine-tunes: 1 - Tags: gguf, code, autocomplete, next-edit ## Links - Model: https://huggingface.co/sweepai/sweep-next-edit-1.5B - Files: https://huggingface.co/sweepai/sweep-next-edit-1.5B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download sweepai/sweep-next-edit-1.5B ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [sweepai/sweep-next-edit-1.5B on Hugging Face](https://huggingface.co/sweepai/sweep-next-edit-1.5B) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Sweep Next-Edit 1.5B (GGUF) (this page) | 1,142 | 341 | 1.4B | apache-2.0 | 2026-01-22 | | [Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF](https://mindket.com/p/06acb609-98ee-4422-8521-7943aeb0bcaa) | 781,625 | 610 | 117B | apache-2.0 | 2026-10-19 | | [Qwen3.5-4B-3D-Coder](https://mindket.com/p/eb4913d2-b5eb-43bf-a0d1-331b5426a5a6) | 392,582 | 1,067 | 4.5B | apache-2.0 | 2026-11-06 | | [Qwen2.5-Coder-7B-Instruct-GGUF](https://mindket.com/p/43397c97-ff69-40bf-92a5-68d176fe394f) | 375,860 | 653 | 7.6B | apache-2.0 | 2024-11-12 | | [DeepSeek-V4.1-Flash-1017-GSQ-RCO-Coder-GGUF](https://mindket.com/p/1350113a-de6f-4d62-96d6-599c30da33a2) | 342,280 | 225 | 197B | mit | 2026-11-02 | | [KAT-Coder-V2.5-Dev GGUF](https://mindket.com/p/e8ca97ed-d610-4d96-bb2f-d351f4b671c4) | 234,191 | 148 | 34.7B | apache-2.0 | 2026-07-24 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · williamzeng0 · 2026-01-21](https://news.ycombinator.com/item?id=46713106): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete: Hey HN, we trained and open-sourced a 1.5B model that predicts your next edits, similar to Cursor. You can download the weights here (https://huggingface.co/sweepai/sweep-next-edit-1.5b) or try it in our JetBrains plugin (https://plugins.jetbrains.com/plugin/26860-sweep-ai-autocomp...). Next-edit… - [Bluesky · Hacker News Companion · 2026-01-23](https://bsky.app/profile/hncompanion.com/post/3md2w6pnmce2n): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete View Article \| Join the HN Conversation Summary of HN discussion 🧵👇 - [Hacker News · atemyipod · 2026-01-27](https://news.ycombinator.com/item?id=46777857): Show HN: Blink-Edit – Cursor-style next-edit predictions for Neovim (local LLMs): Hey HN, we built a pure-Lua Neovim plugin that brings Cursor-style next-edit predictions to Neovim, running entirely on local models. Tab to accept, Esc to reject. GitHub: https://github.com/BlinkResearchLabs/blink-edit.nvim We're Blink Research Labs (https://github.com/BlinkResearchLabs) - an… - [Bluesky · デイリーHuggingFaceトレンド · 2026-01-29](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mdkloyi3kw2x): 今日のHuggingFaceトレンド sweepai/sweep-next-edit-1.5B このリポジトリは、コードエディタの入力補完を行う1.5Bパラメータの言語モデルSweep Next-Editを公開しています。 モデルはGGUF形式で量子化されており、ローカル環境で高速に動作し、小さなサイズながら高性能です。 利用方法や詳細情報はREADMEに記載されています。 - [Hacker News · ihales · 2026-01-23](https://news.ycombinator.com/item?id=46734093): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete: I had Claude add it as an edit-prediction provider (running locally on llama.cpp on my Macbook Pro). It's been working well so far (including next-edit prediction\!), though it could use more testing and tuning. If you want to try it out you can build my branch:… - [Bluesky · 角 征典／Masanori Kado · 2026-01-22](https://bsky.app/profile/kdmsnr.com/post/3md23s6zjxb2l): 🌐次の編集の自動補完用に、HN: スイープ、オープンウェイト 1.5B モデルを表示 https://huggingface.co/sweepai/sweep-next-edit-1.5B via \#HackerNews - [Hacker News · Imustaskforhelp · 2026-01-23](https://news.ycombinator.com/item?id=46733746): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete: I really don't know, I had asked chatgpt to create it and earlier it did give me a wrong one \& I had to try out a lot of things and how it worked on my mac I then pasted that whole convo into aistudio gemini flash to then summarize \& give you the correct settings as my settings included some… - [Bluesky · Hacker News RSS · 2026-01-22](https://bsky.app/profile/hn.rbrt.fr/post/3mcyupnptys2o): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete https://huggingface.co/sweepai/sweep-next-edit-1.5B https://news.ycombinator.com/item?id=46713106 - [Hacker News · kevinlu1248 · 2026-01-23](https://news.ycombinator.com/item?id=46727261): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete: Are you using the right format? https://huggingface.co/sweepai/sweep-next-edit-1.5B/blob/mai... - [Bluesky · Hacker News 250 Points · 2026-01-22](https://bsky.app/profile/newsyc250.bsky.social/post/3mcytut5lnh2t): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete https://huggingface.co/sweepai/sweep-next-edit-1.5B (http://news.ycombinator.com/item?id=46713106) - [Hacker News · kevinlu1248 · 2026-01-23](https://news.ycombinator.com/item?id=46727096): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete: Double-check if you're using the right format. Example here: https://huggingface.co/sweepai/sweep-next-edit-1.5B/blob/mai... - [Bluesky · Hacker News 200 Points · 2026-01-22](https://bsky.app/profile/newsyc200.bsky.social/post/3mcyqirqa562w): Show HN: Sweep, Open-weights 1.5B model for next-edit autocomplete https://huggingface.co/sweepai/sweep-next-edit-1.5B (http://news.ycombinator.com/item?id=46713106) ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-01-22 - First published: 2026-01-20 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open sweepai/sweep-next-edit-1.5B on Hugging Face](https://huggingface.co/sweepai/sweep-next-edit-1.5B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/90acd2a8-17c8-4c4f-be57-b97bd9b0c5f4) - [Its page on Mindket](https://mindket.com/p/90acd2a8-17c8-4c4f-be57-b97bd9b0c5f4)