Instructions to use cortexso/openhermes-2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use cortexso/openhermes-2.5 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 cortexso/openhermes-2.5:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf cortexso/openhermes-2.5:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cortexso/openhermes-2.5:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf cortexso/openhermes-2.5: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 cortexso/openhermes-2.5:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf cortexso/openhermes-2.5: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 cortexso/openhermes-2.5:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf cortexso/openhermes-2.5:Q4_K_M

Use Docker

docker model run hf.co/cortexso/openhermes-2.5:Q4_K_M

LM Studio
Jan

vLLM

How to use cortexso/openhermes-2.5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cortexso/openhermes-2.5"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cortexso/openhermes-2.5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cortexso/openhermes-2.5:Q4_K_M

Ollama
How to use cortexso/openhermes-2.5 with Ollama:
```
ollama run hf.co/cortexso/openhermes-2.5:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use cortexso/openhermes-2.5 with Docker Model Runner:
```
docker model run hf.co/cortexso/openhermes-2.5:Q4_K_M
```

Lemonade

How to use cortexso/openhermes-2.5 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull cortexso/openhermes-2.5:Q4_K_M

Run and chat with the model

lemonade run user.openhermes-2.5-Q4_K_M

List all available models

lemonade list

Atomic Chat

openhermes-2.5 / README.md

jan-ai

Update README.md

e4ef98e verified over 1 year ago

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metadata

license: apache-2.0
pipeline_tag: text-generation
tags:
  - cortex.cpp

Overview

OpenHermes 2.5 Mistral 7B is a state of the art Mistral Fine-tune, a continuation of OpenHermes 2 model, which trained on additional code datasets.

Variants

No	Variant	Cortex CLI command
1	OpenHermes 2.5-7b	`cortex run openhermes-2.5:7b`

Use it with Jan (UI)

Install Jan using Quickstart
Use in Jan model Hub:
```
cortexhub/openhermes-2.5
```

Use it with Cortex (CLI)

Install Cortex using Quickstart
Run the model with command:
```
cortex run openhermes-2.5
```

Credits

Author: Nous Research
Converter: Homebrew
Original License: Licence
Papers: Openhermes 2.5