edtorre/muse-glimmer-agent

edtorre/ muse-glimmer-agent

1 Download Updated 16 hours ago

a 27.9B vision-language model tuned for agentic workflows.

vision

ollama run edtorre/muse-glimmer-agent

curl http://localhost:11434/api/chat \
  -d '{
    "model": "edtorre/muse-glimmer-agent",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='edtorre/muse-glimmer-agent',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'edtorre/muse-glimmer-agent',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Models

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Name

1 model

Size / Usage

Context

Input

muse-glimmer-agent:latest

18GB · 128K context window · Text, Image · 16 hours ago

muse-glimmer-agent:latest

18GB

128K

Text, Image

Readme

Built from muse-glimmer:latest with a 65,536-token context window, this model is configured for use as
an agent (“Hermes”) with step-by-step reasoning, tool calling, and multimodal (vision) capabilities.
Sampling parameters are tuned for reliable, deterministic agent behavior: temperature 0.7, top-p 0.8,
repeat penalty 1.05.

Capabilities: completion · vision · tools · thinking

Use cases: autonomous agents, multi-step task execution, document/image analysis with long context,
function-calling pipelines.