fredrezones55/Jan-code:Q4_K

fredrezones55/ Jan-code:Q4_K_M

82 Downloads Updated 1 week ago

Built on top of Jan-v3-4B-base-instruct; Jan-code is designed to be a practical coding model you can run locally and iterate on quickly—useful for everyday code tasks and as a lightweight “worker” model in agentic workflows.

tools

ollama run fredrezones55/Jan-code:Q4_K_M

curl http://localhost:11434/api/chat \
  -d '{
    "model": "fredrezones55/Jan-code:Q4_K_M",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='fredrezones55/Jan-code:Q4_K_M',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'fredrezones55/Jan-code:Q4_K_M',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Details

Updated 3 weeks ago

3 weeks ago

8045f6a069b0 · 2.7GB ·

model

archqwen3

parameters4.41B

quantizationQ4_K_M

2.7GB

template

13B

params

{ "stop": [ "<|im_start|>", "<|im_end|>" ], "temperature": 0.7, "top

100B

Readme

Jan-Code-4B is a code-tuned model built on top of Jan-v3-4B-base-instruct. It’s designed to be a practical coding model you can run locally and iterate on quickly—useful for everyday code tasks and as a lightweight “worker” model in agentic workflows.

Compared to larger coding models, Jan-Code focuses on handling well-scoped subtasks reliably while keeping latency and compute requirements small.

Intended Use

Lightweight coding assistant for generation, editing, refactoring, and debugging
A small, fast worker model for agent setups (e.g., as a sub-agent that produces patches/tests while a larger model plans)
Replace Haiku model in Claude Code setup