Instructions to use SulphurAI/Sulphur-2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SulphurAI/Sulphur-2-base with Diffusers:

pip install -U diffusers transformers accelerate

import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("SulphurAI/Sulphur-2-base", dtype=torch.bfloat16, device_map="cuda")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]

llama-cpp-python

How to use SulphurAI/Sulphur-2-base with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="SulphurAI/Sulphur-2-base",
	filename="prompt_enhancer/mmproj-BF16.gguf",
)

llm.create_chat_completion(
	messages = "\"A young man walking on the street\""
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use SulphurAI/Sulphur-2-base with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SulphurAI/Sulphur-2-base:BF16
# Run inference directly in the terminal:
llama-cli -hf SulphurAI/Sulphur-2-base:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SulphurAI/Sulphur-2-base:BF16
# Run inference directly in the terminal:
llama-cli -hf SulphurAI/Sulphur-2-base:BF16

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 SulphurAI/Sulphur-2-base:BF16
# Run inference directly in the terminal:
./llama-cli -hf SulphurAI/Sulphur-2-base:BF16

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 SulphurAI/Sulphur-2-base:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SulphurAI/Sulphur-2-base:BF16

Use Docker

docker model run hf.co/SulphurAI/Sulphur-2-base:BF16

LM Studio
Jan
Ollama
How to use SulphurAI/Sulphur-2-base with Ollama:
```
ollama run hf.co/SulphurAI/Sulphur-2-base:BF16
```

Unsloth Studio new

How to use SulphurAI/Sulphur-2-base 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 SulphurAI/Sulphur-2-base 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 SulphurAI/Sulphur-2-base to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SulphurAI/Sulphur-2-base to start chatting

Pi new

How to use SulphurAI/Sulphur-2-base with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf SulphurAI/Sulphur-2-base:BF16

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": "SulphurAI/Sulphur-2-base:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use SulphurAI/Sulphur-2-base with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf SulphurAI/Sulphur-2-base:BF16

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 SulphurAI/Sulphur-2-base:BF16

Run Hermes

hermes

Docker Model Runner
How to use SulphurAI/Sulphur-2-base with Docker Model Runner:
```
docker model run hf.co/SulphurAI/Sulphur-2-base:BF16
```

Lemonade

How to use SulphurAI/Sulphur-2-base with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SulphurAI/Sulphur-2-base:BF16

Run and chat with the model

lemonade run user.Sulphur-2-base-BF16

List all available models

lemonade list

Kabsne commited on 2 days ago

Commit

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Update README.md

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@@ -2,7 +2,7 @@
 library_name: diffusers
 pipeline_tag: text-to-video
 ---
 **Sulphur 2**
 An uncensored video generation model based on LTX 2.3 supporting both t2v and i2v natively, as well as all of the other ltx 2.3 formats.
@@ -11,7 +11,7 @@ Join our  **[Discord](https://discord.gg/GSXJhKZ9V)**
 Support the next version of the project, even just a few dollars would go a long way: **[Kofi](https://ko-fi.com/fusioncow)**
----
 **Get Started:**
 To get started with the model, I recommend downloading either of the dev versions, (fp8mixed or bf16) and downloading the distill lora provided. By the way, I'm aware the workflows contain sulphur_final right now, just use the lora or use the full models, don't use both at the same time.

 library_name: diffusers
 pipeline_tag: text-to-video
 ---
+vb
 **Sulphur 2**
 An uncensored video generation model based on LTX 2.3 supporting both t2v and i2v natively, as well as all of the other ltx 2.3 formats.
 Support the next version of the project, even just a few dollars would go a long way: **[Kofi](https://ko-fi.com/fusioncow)**
+--supp-
 **Get Started:**
 To get started with the model, I recommend downloading either of the dev versions, (fp8mixed or bf16) and downloading the distill lora provided. By the way, I'm aware the workflows contain sulphur_final right now, just use the lora or use the full models, don't use both at the same time.