Instructions to use QuantFactory/OpenHermes-Emojitron-001-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/OpenHermes-Emojitron-001-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/OpenHermes-Emojitron-001-GGUF",
	filename="OpenHermes-Emojitron-001.Q2_K.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 QuantFactory/OpenHermes-Emojitron-001-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/OpenHermes-Emojitron-001-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 QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/OpenHermes-Emojitron-001-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 QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/OpenHermes-Emojitron-001-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 QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/OpenHermes-Emojitron-001-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M
```

Unsloth Studio new

How to use QuantFactory/OpenHermes-Emojitron-001-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 QuantFactory/OpenHermes-Emojitron-001-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 QuantFactory/OpenHermes-Emojitron-001-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/OpenHermes-Emojitron-001-GGUF to start chatting

Docker Model Runner
How to use QuantFactory/OpenHermes-Emojitron-001-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/OpenHermes-Emojitron-001-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/OpenHermes-Emojitron-001-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.OpenHermes-Emojitron-001-GGUF-Q4_K_M

List all available models

lemonade list

QuantFactory/OpenHermes-Emojitron-001-GGUF

This is quantized version of movaxbx/OpenHermes-Emojitron-001 created using llama.cpp

Original Model Card

OpenHermes-Emojitron-001

🧑‍🎓📜🔄🌌➡️🗣️🌠🔮🖊️👀🤝🔄🧩🛠️👂📡🔐🌟

Model description

OpenHermes-Emojitron-001 is a state of the art Emoji Fine-tune, based on the OpenHermes 2.5 model.

It only speaks in emoji. Mostly. If using for chat, start it off with a nice 😊 to get going.

Huge thank you to Teknium and Mistral for a wonderful model.

Follow all my updates in ML and AI on Twitter: https://twitter.com/mov_axbx

Example Outputs
Benchmark Results
Prompt Format
Quantized Models

Example Outputs

Geography knowlege:

in what country is london

🇬🇧

Chat about food:

what country has the best food

🤔🌎🍽️

1️⃣🇮🇳

2️⃣🇯🇵

3️⃣🇺🇸

4️⃣🇪🇸

5️⃣🇫🇷

Talk about movies:

tell me a time travel story about a delorean

🛸🚗🕰️👨‍🔬🔍📅1985👴🚗💭🔜🌌😱💡💼🔢🔜📅1955🚗👨‍👩‍👧‍👦👀🔜🌉🕰️💥🌀🚗🕰️🔂📅1985👨‍🔬🎉

Benchmark Results

There are no benchmarks for emoji models. Maybe someone can create one. EmojiBench 5K let's gooooooo

Prompt Format

OpenHermes-Emojitron-001 uses ChatML as the prompt format, just like Open Hermes 2.5

It also appears to handle Mistral format great. Especially since I used that for the finetune (oops)

Quantized Models:

Coming soon if TheBloke thinks this is worth his 🕰️

Downloads last month: 161

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Providers NEW

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

Model tree for QuantFactory/OpenHermes-Emojitron-001-GGUF

Base model

mistralai/Mistral-7B-v0.1

Finetuned

teknium/OpenHermes-2.5-Mistral-7B

Quantized

(53)

this model

QuantFactory
/

OpenHermes-Emojitron-001-GGUF