Instructions to use py-sandy/MythoMax-L2-13B-GGUF-FP16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use py-sandy/MythoMax-L2-13B-GGUF-FP16 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 py-sandy/MythoMax-L2-13B-GGUF-FP16:F16
# Run inference directly in the terminal:
llama cli -hf py-sandy/MythoMax-L2-13B-GGUF-FP16:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf py-sandy/MythoMax-L2-13B-GGUF-FP16:F16
# Run inference directly in the terminal:
llama cli -hf py-sandy/MythoMax-L2-13B-GGUF-FP16: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 py-sandy/MythoMax-L2-13B-GGUF-FP16:F16
# Run inference directly in the terminal:
./llama-cli -hf py-sandy/MythoMax-L2-13B-GGUF-FP16: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 py-sandy/MythoMax-L2-13B-GGUF-FP16:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf py-sandy/MythoMax-L2-13B-GGUF-FP16:F16

Use Docker

docker model run hf.co/py-sandy/MythoMax-L2-13B-GGUF-FP16:F16

LM Studio
Jan

vLLM

How to use py-sandy/MythoMax-L2-13B-GGUF-FP16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "py-sandy/MythoMax-L2-13B-GGUF-FP16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "py-sandy/MythoMax-L2-13B-GGUF-FP16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/py-sandy/MythoMax-L2-13B-GGUF-FP16:F16

Ollama
How to use py-sandy/MythoMax-L2-13B-GGUF-FP16 with Ollama:
```
ollama run hf.co/py-sandy/MythoMax-L2-13B-GGUF-FP16:F16
```

Unsloth Studio

How to use py-sandy/MythoMax-L2-13B-GGUF-FP16 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 py-sandy/MythoMax-L2-13B-GGUF-FP16 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 py-sandy/MythoMax-L2-13B-GGUF-FP16 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for py-sandy/MythoMax-L2-13B-GGUF-FP16 to start chatting

Docker Model Runner
How to use py-sandy/MythoMax-L2-13B-GGUF-FP16 with Docker Model Runner:
```
docker model run hf.co/py-sandy/MythoMax-L2-13B-GGUF-FP16:F16
```

Lemonade

How to use py-sandy/MythoMax-L2-13B-GGUF-FP16 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull py-sandy/MythoMax-L2-13B-GGUF-FP16:F16

Run and chat with the model

lemonade run user.MythoMax-L2-13B-GGUF-FP16-F16

List all available models

lemonade list

Atomic Chat

YAML Metadata Warning:The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

license: cc-by-nc-4.0 license_name: cc-by-nc-4.0

🧠 MythoMax-L2-13B - GGUF FP16 (Unquantized)

This is a GGUF-converted, float16 version of Gryphe's MythoMax-L2-13B, designed for local inference with full quality on high-VRAM GPUs.

🎙️ Converted & shared by: Sandra Weidmann
🛠️ Tested with: RTX 3090, text-generation-webui + llama.cpp
🔗 Original Model: Gryphe/MythoMax-L2-13B

✨ Why this model?

This model was converted to preserve full precision (float16) for use in:

🧠 fine-tuned instruction tasks
🎭 roleplay and creative writing
💬 emotionally nuanced dialogue
🧪 experimentation with full-context outputs (4096+ tokens)

📦 Model Details

Property	Value
Format	GGUF
Precision	float16 (f16)
Context Size	4096
Tensor Count	363
File Size	~26.0 GB
Original Format	Transformers (`.bin`)
Converted Using	`convert_hf_to_gguf.py`

🧰 Usage (with `llama.cpp`)

./main -m mythomax-l2-13b-f16.gguf -c 4096 -n 512 --color
Or via text-generation-webui:

Backend: llama.cpp

Load model: mythomax-l2-13b-f16.gguf

Set context: 4096+

💙 Notes
This GGUF build is shared for non-commercial, experimental, and educational use.
Full credit to the original model author Gryphe.
If this version helped you, consider giving it a ⭐ and sharing feedback.

Sandra ✨
py-sandy
https://samedia.app/dev

Downloads last month: 33

GGUF

Model size

13B params

Architecture

llama

Hardware compatibility

16-bit

Model tree for py-sandy/MythoMax-L2-13B-GGUF-FP16

Base model

Gryphe/MythoMax-L2-13b

Quantized

(17)