Instructions to use goodasdgood/dracarys2-72b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use goodasdgood/dracarys2-72b-instruct with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="goodasdgood/dracarys2-72b-instruct",
	filename="dracarys2-72b-instruct.gguf-00001-of-00006.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 goodasdgood/dracarys2-72b-instruct with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf goodasdgood/dracarys2-72b-instruct
# Run inference directly in the terminal:
llama-cli -hf goodasdgood/dracarys2-72b-instruct

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf goodasdgood/dracarys2-72b-instruct
# Run inference directly in the terminal:
llama-cli -hf goodasdgood/dracarys2-72b-instruct

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 goodasdgood/dracarys2-72b-instruct
# Run inference directly in the terminal:
./llama-cli -hf goodasdgood/dracarys2-72b-instruct

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 goodasdgood/dracarys2-72b-instruct
# Run inference directly in the terminal:
./build/bin/llama-cli -hf goodasdgood/dracarys2-72b-instruct

Use Docker

docker model run hf.co/goodasdgood/dracarys2-72b-instruct

LM Studio
Jan
Ollama
How to use goodasdgood/dracarys2-72b-instruct with Ollama:
```
ollama run hf.co/goodasdgood/dracarys2-72b-instruct
```

Unsloth Studio new

How to use goodasdgood/dracarys2-72b-instruct 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 goodasdgood/dracarys2-72b-instruct 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 goodasdgood/dracarys2-72b-instruct to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for goodasdgood/dracarys2-72b-instruct to start chatting

Pi new

How to use goodasdgood/dracarys2-72b-instruct with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf goodasdgood/dracarys2-72b-instruct

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "goodasdgood/dracarys2-72b-instruct"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use goodasdgood/dracarys2-72b-instruct with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf goodasdgood/dracarys2-72b-instruct

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default goodasdgood/dracarys2-72b-instruct

Run Hermes

hermes

Docker Model Runner
How to use goodasdgood/dracarys2-72b-instruct with Docker Model Runner:
```
docker model run hf.co/goodasdgood/dracarys2-72b-instruct
```

Lemonade

How to use goodasdgood/dracarys2-72b-instruct with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull goodasdgood/dracarys2-72b-instruct

Run and chat with the model

lemonade run user.dracarys2-72b-instruct-{{QUANT_TAG}}

List all available models

lemonade list

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

!git clone https://github.com/ggerganov/llama.cpp

%cd llama.cpp

!make

!./llama-cli -h

!./llama-gguf-split --split-max-size 5G /content/dracarys2-72b-instruct.Q2_K.gguf dracarys2-72b-instruct.gguf

from huggingface_hub import upload_file

رفع جزء النموذج الأول

upload_file( path_or_fileobj="/content/llama.cpp/dracarys2-72b-instruct.gguf-00001-of-00006.gguf", # استبدل بمسار الجزء الأول path_in_repo="dracarys2-72b-instruct.gguf-00001-of-00006.gguf", # اسم الملف في المستودع repo_id=repo_name, # اسم المستودع )

رفع جزء النموذج الثاني

upload_file( path_or_fileobj="/content/llama.cpp/dracarys2-72b-instruct.gguf-00002-of-00006.gguf", # استبدل بمسار الجزء الثاني path_in_repo="dracarys2-72b-instruct.gguf-00002-of-00006.gguf", # اسم الملف في المستودع repo_id=repo_name, # اسم المستودع )

وهكذا لبقية الأجزاء

!./llama-cli -m "/content/dracarys2-72b-instruct.Q2_K.gguf" -p "who is ai?" -n 50 -e -t 4 --no-warmup

!./bin/llama-cli -m "/content/dracarys2-72b-instruct.Q2_K.gguf" -p "Hi you how are you" -n 50 -e -ngl 33 -t 4

run it !./llama-cli -m "/content/llama.cpp/dracarys2-72b-instruct.gguf-00001-of-00006.gguf" -p "who is ai?" -n 50 -e -t 4 --no-warmup

Downloads last month: 5

GGUF

Model size

73B params

Architecture

qwen2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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