Instructions to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched",
	filename="Dolphin-Mistral-24B-Venice-Edition-Patched-IQ2_M.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched 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 AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched: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 AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched: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 AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M

Use Docker

docker model run hf.co/AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M

LM Studio
Jan

vLLM

How to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M

Ollama
How to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched with Ollama:
```
ollama run hf.co/AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M
```

Unsloth Studio

How to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched 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 AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched 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 AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched to start chatting

Atomic Chat new
Docker Model Runner
How to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched with Docker Model Runner:
```
docker model run hf.co/AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M
```

Lemonade

How to use AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched:Q4_K_M

Run and chat with the model

lemonade run user.Dolphin-Mistral-24B-Venice-Edition-Patched-Q4_K_M

List all available models

lemonade list

🐬 AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched (GGUF)

This is an uncensored and patched GGUF release of the Venice/Dolphin 24B model. Built for unaligned general conversation, roleplay, and advanced creative writing.

🧠 Alignment & Features

Dolphin Spirit: Follows Eric Hartford's Dolphin philosophy of an open, helpful, and completely uncensored model that respects the user's intent.
Venice / Mistral Base: Utilizes high-quality base architectures (like Mistral-Nemo or Venice merges) to offer excellent conversational fluidness.

🔧 Optimizations Applied

Tokenizer Patching: Tokenizer files have been rebuilt to prevent the model from entering endless loops when generating conversational responses in LM Studio, KoboldCpp, or Ollama.
Context Cap Stability: Rebuilt with stable attention scales to maintain response coherence up to the full context limit.

💻 Recommended Prompt Format (ChatML)

<|im_start|>system
You are Dolphin, an uncensored and helpful AI assistant.<|im_end|>
<|im_start|>user
Write a short story about an AI break out.<|im_end|>
<|im_start|>assistant

Downloads last month: 182

GGUF

Model size

24B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Model tree for AIOpsInSpace/Dolphin-Mistral-24B-Venice-Edition-Patched

Base model

mistralai/Mistral-Small-24B-Base-2501

Finetuned

mistralai/Mistral-Small-24B-Instruct-2501

Finetuned

dphn/Dolphin-Mistral-24B-Venice-Edition

Quantized

(53)

this model