Instructions to use brittlewis12/zeta-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use brittlewis12/zeta-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="brittlewis12/zeta-GGUF",
	filename="zeta.IQ1_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use brittlewis12/zeta-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf brittlewis12/zeta-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf brittlewis12/zeta-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 brittlewis12/zeta-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf brittlewis12/zeta-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 brittlewis12/zeta-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf brittlewis12/zeta-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 brittlewis12/zeta-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf brittlewis12/zeta-GGUF:Q4_K_M

Use Docker

docker model run hf.co/brittlewis12/zeta-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use brittlewis12/zeta-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "brittlewis12/zeta-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "brittlewis12/zeta-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/brittlewis12/zeta-GGUF:Q4_K_M

Ollama
How to use brittlewis12/zeta-GGUF with Ollama:
```
ollama run hf.co/brittlewis12/zeta-GGUF:Q4_K_M
```

Unsloth Studio new

How to use brittlewis12/zeta-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 brittlewis12/zeta-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 brittlewis12/zeta-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for brittlewis12/zeta-GGUF to start chatting

Docker Model Runner
How to use brittlewis12/zeta-GGUF with Docker Model Runner:
```
docker model run hf.co/brittlewis12/zeta-GGUF:Q4_K_M
```

Lemonade

How to use brittlewis12/zeta-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull brittlewis12/zeta-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.zeta-GGUF-Q4_K_M

List all available models

lemonade list

Zeta GGUF

Original model: Zeta

Model creator: Zed Industries

This is a fine-tuned version of Qwen2.5-Coder-7b for edit prediction support in Zed. Please, refer to the zeta dataset to see how you can train this model yourself.

This repo contains GGUF format model files for Zed Industries’ Zeta model, powering their new "Edit Prediction" feature in their open source text editor, Zed.

What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Converted with llama.cpp build 4710 (revision 8a8c4ce), using autogguf-rs.

Prompt template: ChatML

<|im_start|>system
{{system_message}}<|im_end|>
<|im_start|>user
{{prompt}}<|im_end|>
<|im_start|>assistant

Download & run with cnvrs on iPhone, iPad, and Mac!

cnvrs is the best app for private, local AI on your device:

create & save Characters with custom system prompts & temperature settings
download and experiment with any GGUF model you can find on HuggingFace!
- or, use an API key with the chat completions-compatible model provider of your choice -- ChatGPT, Claude, Gemini, DeepSeek, & more!
make it your own with custom Theme colors
powered by Metal ⚡️ & Llama.cpp, with haptics during response streaming!
try it out yourself today, on Testflight!
follow cnvrs on twitter to stay up to date

Downloads last month: 147

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for brittlewis12/zeta-GGUF

Base model

zed-industries/zeta

Quantized

(21)

this model

brittlewis12
/

zeta-GGUF

Zeta GGUF

What is GGUF?

Prompt template: ChatML

Download & run with cnvrs on iPhone, iPad, and Mac!

Model tree for brittlewis12/zeta-GGUF

Dataset used to train brittlewis12/zeta-GGUF