Instructions to use ronniealfaro/mythos-prime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ronniealfaro/mythos-prime with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ronniealfaro/mythos-prime", dtype="auto")

HERMES

How to use ronniealfaro/mythos-prime with HERMES:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

llama-cpp-python

How to use ronniealfaro/mythos-prime with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ronniealfaro/mythos-prime",
	filename="mythos.Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use ronniealfaro/mythos-prime with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ronniealfaro/mythos-prime:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf ronniealfaro/mythos-prime:Q4_K_M

Install from WinGet (Windows)

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

Use Docker

docker model run hf.co/ronniealfaro/mythos-prime:Q4_K_M

LM Studio
Jan
Ollama
How to use ronniealfaro/mythos-prime with Ollama:
```
ollama run hf.co/ronniealfaro/mythos-prime:Q4_K_M
```

Unsloth Studio new

How to use ronniealfaro/mythos-prime 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 ronniealfaro/mythos-prime 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 ronniealfaro/mythos-prime to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ronniealfaro/mythos-prime to start chatting

Docker Model Runner
How to use ronniealfaro/mythos-prime with Docker Model Runner:
```
docker model run hf.co/ronniealfaro/mythos-prime:Q4_K_M
```

Lemonade

How to use ronniealfaro/mythos-prime with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ronniealfaro/mythos-prime:Q4_K_M

Run and chat with the model

lemonade run user.mythos-prime-Q4_K_M

List all available models

lemonade list

🧿 Mythos Prime — A LoRA-Fused GGUF Model

Author: Ronnie Alfaro (@ronniealfaro)
Base model: NousResearch/Hermes-2-Pro-Mistral-7B
Fused using PEFT + merge_and_unload, converted with llama.cpp.

📜 Model Description

Mythos Prime is a fine-tuned fusion of the powerful Hermes 2 Pro (Mistral 7B) base model with a LoRA adapter trained on mythological, symbolic, and philosophical prompts across global traditions.

This model blends Hermes’ natural coherence with a deep narrative capacity focused on:

🧠 Storytelling with archetypal structure
📚 Myth interpretation and symbolic exploration
💬 Philosophical discourse generation
🎮 Lore-rich worldbuilding for fiction & games
✍️ Creative writing inspired by ancient motifs

🛠️ Technical Specs

Feature	Value
Base model	`NousResearch/Hermes-2-Pro-Mistral-7B`
Adapter type	LoRA (`peft_type: LORA`)
Merge method	`merge_and_unload()` via PEFT
Output formats	`.gguf (f16)` + `.gguf (Q4_K_M)`
Tokenizer	Hermes original tokenizer
Context length	4096 tokens

🔍 Files Included

Filename	Description
`mythos.gguf`	Fused full-precision model (f16)
`mythos.Q4_K_M.gguf`	Quantized version (Q4_K_M)
`tokenizer.model/json`	Tokenizer for Hermes
`config.json`	Base model config

🧪 Intended Use

Mythos Prime was created for use in:

Writing and storytelling based on mythic structures
Narrative AI assistants with symbolic insight
Philosophical or metaphysical exploration
Games and RPG tools for generating lore, pantheons, or quests
Worldbuilding that draws from multiple cultural traditions

⚠️ Limitations

May produce abstract, symbolic, or obscure outputs — this is by design
Not tuned for factual accuracy or real-time knowledge
May reflect cultural biases from training data

🗿 Credits & Lore

Fused by Ronnie Alfaro, after wrestling with Axolotl, its examples.yaml minion, the import-loop cyclops, and the blue screen oracle of pain.

This model is a techno-mystical artifact of patience, recursion, and narrative passion.

🔮 License

Follows the base model license: Apache 2.0

Downloads last month: 107

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

4-bit

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