Instructions to use olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF",
	filename="nous-hermes-2-mistral-7b-dpo.Q4_0.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-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 olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0
# Run inference directly in the terminal:
llama cli -hf olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0
# Run inference directly in the terminal:
llama cli -hf olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0

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 olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0

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 olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0

Use Docker

docker model run hf.co/olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0

LM Studio
Jan
Ollama
How to use olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF with Ollama:
```
ollama run hf.co/olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0
```

Unsloth Studio

How to use olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-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 olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-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 olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF with Docker Model Runner:
```
docker model run hf.co/olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0
```

Lemonade

How to use olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull olafgeibig/Nous-Hermes-2-Mistral-7B-DPO-GGUF:Q4_0

Run and chat with the model

lemonade run user.Nous-Hermes-2-Mistral-7B-DPO-GGUF-Q4_0

List all available models

lemonade list

Nous-Hermes-2-Mistral-7B-DPO-GGUF

File size: 1,114 Bytes

---
base_model: mistralai/Mistral-7B-v0.1
tags:
- Mistral
- instruct
- finetune
- chatml
- DPO
- RLHF
- gpt4
- synthetic data
- distillation
model-index:
- name: Nous-Hermes-2-Mistral-7B-DPO
  results: []
license: apache-2.0
language:
- en
datasets:
- teknium/OpenHermes-2.5
---
# Nous-Hermes-2-Mistral-7B-DPO

I converted [NousResearch/Nous-Hermes-2-Mistral-7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO) to GGUF and quantized it to my favorite quantizations. Se their original model card for all the details. 

I quickly quantized this model using a modified version of [AutoGGUF](https://t.co/oUuxN2fvSX) from [Maxime Labonne](https://huggingface.co/mlabonne)

Here is my Ollama modelfile. According to llama.cpp the model was trained on 32k tokens, but I set the ollama modelfile to 16k so that 16 GB Macs can still run it.
```
FROM ./nous-hermes-2-mistral-7b-dpo.Q5_K_M.gguf
PARAMETER num_ctx 16384
TEMPLATE """<|im_start|>system
{{ .System }}<|im_end|>
<|im_start|>user
{{ .Prompt }}<|im_end|>
<|im_start|>assistant
"""
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|im_end|>"
```