Instructions to use Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF",
	filename="GGUF/MythoMist-AshhLimaRP-Mistral-7B-Q4_K_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 Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Herman555/MythoMist-AshhLimaRP-Mistral-7B-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 Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Herman555/MythoMist-AshhLimaRP-Mistral-7B-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 Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Herman555/MythoMist-AshhLimaRP-Mistral-7B-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 Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF with Ollama:
```
ollama run hf.co/Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use Herman555/MythoMist-AshhLimaRP-Mistral-7B-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 Herman555/MythoMist-AshhLimaRP-Mistral-7B-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 Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF to start chatting

Docker Model Runner
How to use Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF with Docker Model Runner:
```
docker model run hf.co/Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M
```

Lemonade

How to use Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Herman555/MythoMist-AshhLimaRP-Mistral-7B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.MythoMist-AshhLimaRP-Mistral-7B-GGUF-Q4_K_M

List all available models

lemonade list

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

Author of model: Addendum (2023-11-23): A more thorough investigation revealed a flaw in my original algorithm that has since been resolved. I've debated deleting this model as it did not follow its original objective but since there are plenty of folks enjoying it I'll be keeping it around.

Herman555: I will update this repository with fixed model as soon as it is available.

Downloads last month: 47

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

8-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support