Qwen2.5 Coder 14B (AWQ)

Code-specialised Qwen model for completion, generation and repair across dozens of languages.

Overview

Qwen2.5 Coder was trained on a large code corpus and is a popular self-hosted backend for coding assistants. Point any OpenAI-compatible IDE plugin at your rental's API URL.

Key features

• ✓
  OpenAI-compatible — works with IDE plugins
• ✓
  32K context
• ✓
  Apache 2.0

Use cases

• →
  Private coding assistant
• →
  Code review bots
• →
  Generating tests and docs

On this template

Runs on the vLLM (OpenAI-compatible API) template, exposing its OpenAI-compatible API at a private HTTPS address. You also get root SSH and JupyterLab.

MODEL_ID	Qwen/Qwen2.5-Coder-14B-Instruct-AWQ
VLLM_ARGS	--max-model-len 32768 --gpu-memory-utilization 0.90

Quick start

1. Click Deploy and pick an available GPU — only offers with enough VRAM are shown.
2. Wait for the status to turn running. The first start downloads the model, which can take a few minutes.
3. Use the connection details on your rental page:

curl https://r12-abcd1234-app.gpu.clearlayer.ca/v1/chat/completions \
  -H "Authorization: Bearer <app-token>" \
  -H "Content-Type: application/json" \
  -d '{"model": "Qwen/Qwen2.5-Coder-14B-Instruct-AWQ", "messages": [{"role": "user", "content": "Hello!"}]}'

from openai import OpenAI

client = OpenAI(base_url="https://r12-abcd1234-app.gpu.clearlayer.ca/v1", api_key="<app-token>")
resp = client.chat.completions.create(
    model="Qwen/Qwen2.5-Coder-14B-Instruct-AWQ",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(resp.choices[0].message.content)