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

HOWW TO DOWNLOAD AND USE ON COMFYUI HELP PLEEASEE

#21

by JesusKill - opened 16 days ago

Discussion

JesusKill

16 days ago

how???

adeebaldkheel

16 days ago

https://chat.mistral.ai/chat/5f09ed72-559f-4c46-b734-87c965ee8ac9

cutecommando

13 days ago

how to download any application please giude me i don't know how to download

Smite79

10 days ago

how to download any application please giude me i don't know how to download

Huggingface isn't for spoon-feeding. Go find some tutorials on YouTube that will tell you how to use the model. The forums are for discussion and bug reporting.

KLL1111

8 days ago

•

edited 8 days ago

I'm confused.
What should I download?
I downloaded sulphur_dev_fp8mixed because it's the smallest.
But in the examples, it's ltx-2.3-22b-dev-fp8
Do I need to download that too? Or can I use sulphur_dev_fp8mixed instead?
I don't understand.

What's this?
ltx-2.3-22b-distilled-lora-384
What's this?
ltx-2.3-22b-distilled-lora-1.1_fro90_celi72_condsafe
And I don't even know where to get this:
sulphur_final

And what's this?
sulphur_lora_rank_768

And how to connect them together is unclear; half the blocks are disabled.
I understand that something is already sewn somewhere or not sewn, something is for speed, but the names are completely unclear.
No explanation.
Has anyone figured this out?

Vlad123983

4 days ago

What should I download?
I downloaded sulphur_dev_fp8mixed because it's the smallest.
But in the examples, it's ltx-2.3-22b-dev-fp8
Do I need to download that too? Or can I use sulphur_dev_fp8mixed instead?

use sulphur_dev_fp8mixed anywhere instead of ltx-2.3-22b-dev-fp8
lora_rank_768 (it's a sulfur_final) is already implemented in sulphur_dev_fp8mixed, so you don't need it.

What's this?
ltx-2.3-22b-distilled-lora-384

You can try this as lora with strength 0.4-0.5 for the First Sampler (in Low Resolution), but it seems useless.

ltx-2.3-22b-distilled-lora-1.1_fro90_celi72_condsafe

Use this as lora with strength 0.5 for the 2nd Sampler (in High Resolution).

gemma_3_12B_it_fp4_mixed, spatial_upscaler and taeltx2_3 you can recieve from almost any other LTX workflows.

KLL1111

3 days ago

It doesn't work. Terrible results. And the sound is ruined 50% of the time.

But I liked prompt_enhancer. I attached it to wan2.2_REMIX. However, I still have a question about how to set it up correctly. It's unclear which system/user prompt/prompt template/sampling settings are best for it, so I have to try and find them.

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