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 Settings

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

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

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 28 days ago

Discussion

JesusKill

28 days ago

how???

adeebaldkheel

28 days ago

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

cutecommando

25 days ago

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

Smite79

22 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

20 days ago

•

edited 20 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

16 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

15 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.

Phac321

5 days ago

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

its a you problem buddy xD maybe learn about how the stuff actually works. This is not the place for that. Ask an AI.

KLL1111

5 days ago

maybe learn about how the stuff actually works.

Then why does everything work for wan2.2 and in 90% of cases I get what I want?

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment