shipwithmuse

Entries matching “python”

9 builds · page 1 of 1

Matt Deitke

@mattdeitke

Excited to share Muse Spark! It's a strong natively multimodal model with many surprising properties that emerged. Here, the model is able to use Python tools to make a playable Sudoku game on the web from an image input of the board. ✨

X post · Games & 3D· ♥ 179

Playable Sudoku from a board photo

@vcspr

@vcspr

Unofficial terminal skill for Muse that calls the Apify API to list actors, start runs, poll status and pull dataset items from a single stdlib-only Python CLI.

Skill · Connectors & MCP

Apify skill for Muse

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tacticaltweaker

u/tacticaltweaker

I'm just using OpenWebUI with a simple FastMCP server. Every other model I've tried will simply run a few lines of Python and give me the result. Glimmer seems to overthink like crazy to the point of being useless. On the carwash test it tried to compute emissions using Python. I'm using the recommended sampling parameters, default template, and I've tried both unsloth's Q6_K_XL and Meta's dynamic GGUFs. Any ideas? EDIT: It seems like it's definitely related to the tools available. With them disabled, it's reasonably efficient. I guess it's just overly eager to call every tool it can unlike Qwen or Gemma in my experience.

Reddit post · Benchmarks & research

Glimmer over-eager with MCP tools

@hoziertom44-arch

@hoziertom44-arch

A Python bot for Binance USDT-M futures, built with Meta AI's Muse Spark, that trades ETH inversely when BTC and ETH show strong opposite 9/21 EMA trends on 5-minute candles.

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OkSea7809

u/OkSea7809

Hi all, I'm a newbie and trying to assess the performance of some LLMs I'm running locally via oMLX on my MacBook Pro M5pro CPU 15 cores (5 Super and 10 Performance), GPU 16 cores and 48 GB of LPDDR5 RAM. I asked chatGPT guidance to run some tests and check whether the DFlash-based drafter Muse-Glimmer-30B-Assistant might somewhat speedup the base model Muse-Glimmer-30B-4bit. The results show no or negligible improvement with active DFlash acceleration (speedup between 0.90% and 1.16%). The test was structured with three different prompts fed to both the baseline and the dflash-capable model profiles: Technical prose; Python code; Structured JSON a cap of 2048 tokens, no cache, temperature=0. Each inference was repeated three times. Anyone have similar experience? can we simply dump the Assistant as not useful in this hw/sw configuration?

Reddit post · Local & open models

Testing the Glimmer DFlash drafter on an M5 Mac

@evangit2

@evangit2

A pure-stdlib Python proxy that exposes Meta API access to Muse Spark through OpenAI-compatible endpoints for tools like OpenCode and Hermes, with no muse CLI required.

GitHub · Coding & dev tools· ★ 1

muse-sub-proxy

Your product

Sponsored

Put your logo, a line of copy and an image right here, between the builds Muse developers come to read. Same size as a post.

$100/week

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Shown every 12 builds · on every catalog page

@rajkumar898

@rajkumar898

An educational ~1,600-line Python chat app on Muse Spark that finds papers, reads PDFs and writes a cited report only after the user clicks Approve, built to show students how an LLM app becomes an agent.

GitHub · Agents & automation

Mini-Muse research agent

@krtarunsingh

@krtarunsingh

An experiment running Muse Glimmer 30B Q4_K_M via llama.cpp on an RTX 4060 laptop with 8 GB VRAM, testing autonomous Python bug fixing, tool-failure recovery and multimodal invoice extraction.

GitHub · Local & open models

Muse Glimmer on an 8 GB RTX 4060 laptop

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build.nvidia.com

build.nvidia.com

NVIDIA hosts a Muse Glimmer 30B endpoint on build.nvidia.com with Python (OpenAI, LangChain), JavaScript and curl examples for the ~29.6B multimodal model with 131K context.

Site · Local & open models

Muse Glimmer 30B on NVIDIA build