Instructions to use zai-org/glm-edge-v-2b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use zai-org/glm-edge-v-2b-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf zai-org/glm-edge-v-2b-gguf:Q4_K_M

Use Docker

docker model run hf.co/zai-org/glm-edge-v-2b-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use zai-org/glm-edge-v-2b-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/glm-edge-v-2b-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/glm-edge-v-2b-gguf",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/zai-org/glm-edge-v-2b-gguf:Q4_K_M

Ollama
How to use zai-org/glm-edge-v-2b-gguf with Ollama:
```
ollama run hf.co/zai-org/glm-edge-v-2b-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use zai-org/glm-edge-v-2b-gguf with Docker Model Runner:
```
docker model run hf.co/zai-org/glm-edge-v-2b-gguf:Q4_K_M
```

Lemonade

How to use zai-org/glm-edge-v-2b-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull zai-org/glm-edge-v-2b-gguf:Q4_K_M

Run and chat with the model

lemonade run user.glm-edge-v-2b-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

glm-edge-v-2b-gguf / README_zh.md

test

d76cbe1 almost 2 years ago

preview code

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Glm-Edge-V-2B-GGUF

使用ollama 推理

安装

目前针对该模型的适配代码正在积极合入官方llama.cpp中,可通过下述适配版本进行测试：

git clone https://github.com/piDack/llama.cpp -b support_glm_edge_model
cmake -B build -DGGML_CUDA=ON # 或开启其他加速硬件
cmake --build build -- -j

推理

安装完成后，您可以通过以下命令启动GLM-Edge Chat模型：

llama-llava-cli -m model_path/ggml-model-f16.gguf --mmproj model_path/mmproj-model-f16.gguf --image img_path/image.jpg -p "<|system|>\n system prompt <image><|user|>\n prompt <|assistant|>\n"

在命令行界面，您可以与模型进行交互，输入您的需求，模型将为您提供相应的回复。

协议

本模型的权重的使用则需要遵循 LICENSE。