Instructions to use appvoid/arco-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use appvoid/arco-chat with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("appvoid/arco-chat", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use appvoid/arco-chat 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 appvoid/arco-chat:F16
# Run inference directly in the terminal:
llama cli -hf appvoid/arco-chat:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf appvoid/arco-chat:F16
# Run inference directly in the terminal:
llama cli -hf appvoid/arco-chat:F16

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 appvoid/arco-chat:F16
# Run inference directly in the terminal:
./llama-cli -hf appvoid/arco-chat:F16

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 appvoid/arco-chat:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf appvoid/arco-chat:F16

Use Docker

docker model run hf.co/appvoid/arco-chat:F16

LM Studio
Jan
Ollama
How to use appvoid/arco-chat with Ollama:
```
ollama run hf.co/appvoid/arco-chat:F16
```

Unsloth Studio

How to use appvoid/arco-chat 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 appvoid/arco-chat 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 appvoid/arco-chat to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for appvoid/arco-chat to start chatting

Docker Model Runner
How to use appvoid/arco-chat with Docker Model Runner:
```
docker model run hf.co/appvoid/arco-chat:F16
```

Lemonade

How to use appvoid/arco-chat with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull appvoid/arco-chat:F16

Run and chat with the model

lemonade run user.arco-chat-F16

List all available models

lemonade list

Atomic Chat

arco-chat / README.md

appvoid

Update README.md

34a6b15 verified 11 months ago

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	---
	base_model: appvoid/arco-chat-merged-3
	library_name: transformers
	tags:
	- mergekit
	- merge
	- llama-cpp
	- gguf-my-repo
	---

	# arco-chat
	Model creator: [appvoid](https://huggingface.co/appvoid)<br/>
	GGUF quantization: provided by [appvoid](https:/huggingface.co/appvoid) using `llama.cpp`<br/>
	## Special thanks
	🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
	## Use with Ollama
	```bash
	ollama run "hf.co/appvoid/arco-chat:<quantization>"
	```
	## Use with LM Studio
	```bash
	lms load "appvoid/arco-chat"
	```
	## Use with llama.cpp CLI
	```bash
	llama-cli --hf-repo "appvoid/arco-chat" --hf-file "arco-chat-F16.gguf" -p "The meaning to life and the universe is"
	```
	## Use with llama.cpp Server:
	```bash
	llama-server --hf-repo "appvoid/arco-chat" --hf-file "arco-chat-F16.gguf" -c 4096
	```