Instructions to use QuantFactory/Arcee-Agent-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/Arcee-Agent-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/Arcee-Agent-GGUF",
	filename="Arcee-Agent.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use QuantFactory/Arcee-Agent-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/Arcee-Agent-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Arcee-Agent-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/Arcee-Agent-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Arcee-Agent-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 QuantFactory/Arcee-Agent-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Arcee-Agent-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 QuantFactory/Arcee-Agent-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Arcee-Agent-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/Arcee-Agent-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use QuantFactory/Arcee-Agent-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "QuantFactory/Arcee-Agent-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": "QuantFactory/Arcee-Agent-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/QuantFactory/Arcee-Agent-GGUF:Q4_K_M

Ollama
How to use QuantFactory/Arcee-Agent-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/Arcee-Agent-GGUF:Q4_K_M
```

Unsloth Studio new

How to use QuantFactory/Arcee-Agent-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for QuantFactory/Arcee-Agent-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for QuantFactory/Arcee-Agent-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/Arcee-Agent-GGUF to start chatting

Docker Model Runner
How to use QuantFactory/Arcee-Agent-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/Arcee-Agent-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/Arcee-Agent-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/Arcee-Agent-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Arcee-Agent-GGUF-Q4_K_M

List all available models

lemonade list

munish0838 commited on Jul 20, 2024

Commit

ff626e9

verified ·

1 Parent(s): 30b33b4

Update README.md

Browse files

Files changed (1) hide show

README.md +3 -4

README.md CHANGED Viewed

@@ -1,12 +1,11 @@
 ---
 license: apache-2.0
 language:
 - en
 - de
 - ar
 ---
 ![](https://cdn.discordapp.com/attachments/791342238541152306/1264099835221381251/image.png?ex=669ca436&is=669b52b6&hm=129f56187c31e1ed22cbd1bcdbc677a2baeea5090761d2f1a458c8b1ec7cca4b&)
@@ -164,4 +163,4 @@ You may call them like this:
 Here are the tools available:
 <tools>
-```

 ---
 license: apache-2.0
 language:
 - en
 - de
 - ar
+pipeline_tag: text-generation
+base_model: arcee-ai/Arcee-Agent
 ---
 ![](https://cdn.discordapp.com/attachments/791342238541152306/1264099835221381251/image.png?ex=669ca436&is=669b52b6&hm=129f56187c31e1ed22cbd1bcdbc677a2baeea5090761d2f1a458c8b1ec7cca4b&)
 Here are the tools available:
 <tools>
+```