Instructions to use nold/OpenHermes-Emojitron-001-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use nold/OpenHermes-Emojitron-001-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 nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf nold/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 serve -hf nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf nold/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 nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf nold/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 nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M
Use Docker
docker model run hf.co/nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use nold/OpenHermes-Emojitron-001-GGUF with Ollama:
ollama run hf.co/nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use nold/OpenHermes-Emojitron-001-GGUF with Docker Model Runner:
docker model run hf.co/nold/OpenHermes-Emojitron-001-GGUF:Q4_K_M
- Lemonade
How to use nold/OpenHermes-Emojitron-001-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull nold/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
- Atomic Chat
File size: 2,119 Bytes
fe45776 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | ---
base_model: teknium/OpenHermes-2.5-Mistral-7B
tags:
- mistral
- instruct
- finetune
- chatml
model-index:
- name: OpenHermes-Emojitron-001
results: []
license: apache-2.0
language:
- en
---
# OpenHermes-Emojitron-001

*๐งโ๐๐๐๐โก๏ธ๐ฃ๏ธ๐ ๐ฎ๐๏ธ๐๐ค๐๐งฉ๐ ๏ธ๐๐ก๐๐*
## 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 ๐ 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
# Table of Contents
1. [Example Outputs](#example-outputs)
- [Geography knowlege](#geography)
- [Chat about food](#food-chat)
- [Talk about movies](#movie-talk)
2. [Benchmark Results](#benchmark-results)
3. [Prompt Format](#prompt-format)
4. [Quantized Models](#quantized-models)
## Example Outputs
### Geography knowlege:
in what country is london
```
๐ฌ๐ง
```
### Chat about food:
what country has the best food
```
๐ค๐๐ฝ๏ธ
1๏ธโฃ๐ฎ๐ณ
2๏ธโฃ๐ฏ๐ต
3๏ธโฃ๐บ๐ธ
4๏ธโฃ๐ช๐ธ
5๏ธโฃ๐ซ๐ท
```
### Talk about movies:
tell me a time travel story about a delorean
```
๐ธ๐๐ฐ๏ธ๐จโ๐ฌ๐๐
1985๐ด๐๐ญ๐๐๐ฑ๐ก๐ผ๐ข๐๐
1955๐๐จโ๐ฉโ๐งโ๐ฆ๐๐๐๐ฐ๏ธ๐ฅ๐๐๐ฐ๏ธ๐๐
1985๐จโ๐ฌ๐
```
## 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 ๐ฐ๏ธ
***
Vanilla Quantization by [nold](https://huggingface.co/nold), Model by [OpenHermes-Emojitron-001](https://huggingface.co/movaxbx/OpenHermes-Emojitron-001)
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