rhundt/GLM-4-0414-32b-128k-Q4_K

rhundt/ GLM-4-0414-32b-128k-Q4_K_M

1,071 Downloads Updated 11 months ago

GLM-4-0414 32B with 128k context (YaRN RoPE scaling). Needs ollama 0.6.6

tools

ollama run rhundt/GLM-4-0414-32b-128k-Q4_K_M

curl http://localhost:11434/api/chat \
  -d '{
    "model": "rhundt/GLM-4-0414-32b-128k-Q4_K_M",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='rhundt/GLM-4-0414-32b-128k-Q4_K_M',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'rhundt/GLM-4-0414-32b-128k-Q4_K_M',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Applications

Claude Code ollama launch claude --model rhundt/GLM-4-0414-32b-128k-Q4_K_M

Codex ollama launch codex --model rhundt/GLM-4-0414-32b-128k-Q4_K_M

OpenCode ollama launch opencode --model rhundt/GLM-4-0414-32b-128k-Q4_K_M

OpenClaw ollama launch openclaw --model rhundt/GLM-4-0414-32b-128k-Q4_K_M

Models

View all →

Name

1 model

Size

Context

Input

GLM-4-0414-32b-128k-Q4_K_M:latest

20GB · 32K context window · Text · 11 months ago

GLM-4-0414-32b-128k-Q4_K_M:latest

20GB

32K

Text

Readme

Quantized with YaRN RoPE scaling to 128k context (factor 4). This needs Ollama >=0.6.6 to run. The num_ctx in the Modelfile defaults to 64k just because I don’t have gobs of VRAM.