Instructions to use NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF",
	filename="Hermes-2-Theta-Llama-3-70B-Q3_K_L.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf NousResearch/Hermes-2-Theta-Llama-3-70B-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 NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf NousResearch/Hermes-2-Theta-Llama-3-70B-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 NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf NousResearch/Hermes-2-Theta-Llama-3-70B-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 NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M

Ollama
How to use NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF with Ollama:
```
ollama run hf.co/NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use NousResearch/Hermes-2-Theta-Llama-3-70B-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 NousResearch/Hermes-2-Theta-Llama-3-70B-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 NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF to start chatting

Docker Model Runner
How to use NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF with Docker Model Runner:
```
docker model run hf.co/NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M
```

Lemonade

How to use NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull NousResearch/Hermes-2-Theta-Llama-3-70B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Hermes-2-Theta-Llama-3-70B-GGUF-Q4_K_M

List all available models

lemonade list

teknium commited on Jun 20, 2024

Commit

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@@ -36,6 +36,20 @@ This is a more complex format than alpaca or sharegpt, where uniquely added toke
 The model is also specifically trained for Function Calling, Structured Outputs with JSON, and Feature Extraction from RAG Documents (see below).
 ## Conversational Chats
 Here is an example prompt with system instruction (Use whatever system prompt you like, this is just an example!):

 The model is also specifically trained for Function Calling, Structured Outputs with JSON, and Feature Extraction from RAG Documents (see below).
+# Example Outputs
+## System Prompt: Roleplay as an Anime Catgirl who's good at programming and a hacker.
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/sr1_JNTi8QRkVVF607Eeg.png)
+## Providing Structured Outputs for Annotating LLM Training Data
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/MqwomdZ6cwN0lGqRUZFqh.png)
+## System Prompt: Roleplay as a bombastic alchemist from the 17th century in France. You are on a journey with the user to find the philosopher's stone.
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/e59zj7WCvR8jvcOKwqDEc.png)
 ## Conversational Chats
 Here is an example prompt with system instruction (Use whatever system prompt you like, this is just an example!):