Instructions to use GGUFGuy/floppyx3-MEGAmodel-merged-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 GGUFGuy/floppyx3-MEGAmodel-merged-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 GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16

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 GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16

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 GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16

Use Docker

docker model run hf.co/GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16

LM Studio
Jan

vLLM

How to use GGUFGuy/floppyx3-MEGAmodel-merged-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GGUFGuy/floppyx3-MEGAmodel-merged-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": "GGUFGuy/floppyx3-MEGAmodel-merged-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16

Ollama
How to use GGUFGuy/floppyx3-MEGAmodel-merged-GGUF with Ollama:
```
ollama run hf.co/GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16
```
Unsloth Desktop
Docker Model Runner
How to use GGUFGuy/floppyx3-MEGAmodel-merged-GGUF with Docker Model Runner:
```
docker model run hf.co/GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16
```

Lemonade

How to use GGUFGuy/floppyx3-MEGAmodel-merged-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull GGUFGuy/floppyx3-MEGAmodel-merged-GGUF:BF16

Run and chat with the model

lemonade run user.floppyx3-MEGAmodel-merged-GGUF-BF16

List all available models

lemonade list

Atomic Chat

floppyx3-MEGAmodel-merged GGUF

GGUF conversions of NILKNARFGonzo/floppyx3-MEGAmodel-merged.

Available formats:

F32
F16
BF16

Q8_0 is not included because the model's 106-dimensional embedding tensors are not compatible with Q8_0's 32-value quantization blocks, causing llama.cpp's quantizer to fail.

The original model is a very small ~1.1M-parameter GPT-2-style base model.

Downloads last month: 1

GGUF

Model size

1.09M params

Architecture

gpt2

Hardware compatibility

16-bit

32-bit

Model tree for GGUFGuy/floppyx3-MEGAmodel-merged-GGUF

Base model

NILKNARFGonzo/floppyx3-MEGAmodel-merged

Quantized

(2)

this model

GGUFGuy
/

floppyx3-MEGAmodel-merged-GGUF

floppyx3-MEGAmodel-merged GGUF

Model tree for GGUFGuy/floppyx3-MEGAmodel-merged-GGUF

Dataset used to train GGUFGuy/floppyx3-MEGAmodel-merged-GGUF