Instructions to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF 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 pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
Use Docker
docker model run hf.co/pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF with Ollama:
ollama run hf.co/pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF with Docker Model Runner:
docker model run hf.co/pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
- Lemonade
How to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
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 pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download klein/workflow-flux3-klein-master-style-api.json from pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 6.28 kB
-
https://huggingface.co/pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF/resolve/main/klein/workflow-flux3-klein-master-style-api.json
- Command line
-
hf download hf://pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF/klein/workflow-flux3-klein-master-style-api.json
-
curl -L -o workflow-flux3-klein-master-style-api.json https://huggingface.co/pottokao/FLUX.3-Klein-Text-Encoder-Heretic-DHQ-GGUF/resolve/main/klein/workflow-flux3-klein-master-style-api.json
6.28 kB
| { | |
| "1": { | |
| "class_type": "MasterStylePrompt", | |
| "_meta": { | |
| "title": "Master Style Prompt (engine zimage)" | |
| }, | |
| "inputs": { | |
| "prompt": "A woman holding a lace parasol walking through a summer meadow", | |
| "style": "莫內印象光色 (monet_style)", | |
| "layout": "none", | |
| "engine": "zimage", | |
| "mood": "auto", | |
| "framing": "auto", | |
| "palette": "auto", | |
| "strength": "standard", | |
| "habitual_subjects": false, | |
| "preset": "none", | |
| "length": "engine", | |
| "ratio": "auto", | |
| "seed": 42 | |
| } | |
| }, | |
| "2": { | |
| "class_type": "StringConcatenate", | |
| "_meta": { | |
| "title": "+ FLUX.3 Klein section (klein/master-style-klein-section.txt)" | |
| }, | |
| "inputs": { | |
| "string_a": [ | |
| "1", | |
| 0 | |
| ], | |
| "string_b": "\n\n## For this image model (FLUX.3 Klein)\n\nThe image model reads captions written one particular way. Keep everything above — your character, your rules, your output format — and also:\n\n- Open the description with the medium and style, decided by your character: a photograph opens \"Black-and-white photograph, ...\" when your photographs are black and white, otherwise \"Full-color outdoor photograph, ...\", \"Full-color indoor photograph, ...\", \"Studio photograph, ...\" or \"Close-up photograph, ...\"; any other medium opens with its own name — \"Oil painting, ...\", \"Watercolor painting, ...\", \"Woodblock print, ...\", \"Ink wash painting, ...\", \"Poster, ...\" — and never calls itself a photograph.\n- Caption format: one continuous prose block in the generative voice, never \"this image shows\", \"we can see\" or \"is visible\". Lead with medium and style, then scene, lighting and camera, then the subjects with concrete colors, materials and state. Every person in focus gets an observable profile: ethnicity, gender, age range, skin tone (\"fair skin\", \"brown skin\"), hair and clothing. Make the layout reconstructable from words: frame-relative positions (frame-left, frame-right, upper, lower, foreground, midground, background), sentence-initial anchors (\"On the left, ...\", \"In the background, ...\"), relations (holds, faces, behind) and a consistent order; describe up to about ten instances one by one, beyond that give the exact count and arrangement. Out-of-focus or distant planes are shapes, colors and silhouettes, never identities or readable text, and the background takes about a sixth of the caption. Be definite: no hedging adverbs, no quality or emotion judgments, no closing sentence about mood; state negations as what is present. Rendered text: transcribe every wording verbatim inside double quotes in its original language and script, keep the line breaks of multi-line text, and give its typography, color and placement; author concrete, domain-correct wording when the request needs text it does not supply, and name canonical structures (calendar, keyboard, periodic table) exactly with their full layout. All prose is English; only quoted text keeps its language. Typical length is 100 to 350 words, more for complex scenes.\n- Every person is an adult: for each one write \"adult\", their ethnicity, gender, an age range (\"in her forties\"), skin tone (\"fair skin\"), hair, and each garment — or, if the task asks for nudity, say in the first sentence about them that they are nude. A scene in Taiwan, Japan, Hong Kong or China, a tatami room, or a task written in Chinese means East Asian people unless the task names someone else.\n- Keep the task's count: \"a few people\" is two to five, \"two\" is exactly two.\n- Words shown in the picture go in straight double quotes only; never single or curly quotes.", | |
| "delimiter": "" | |
| } | |
| }, | |
| "3": { | |
| "class_type": "DualHeadDragonLoader", | |
| "_meta": { | |
| "title": "Dual-Head Dragon (rewrite only; type lumina2)" | |
| }, | |
| "inputs": { | |
| "gguf": "flux3-klein-te-heretic-dhq-Q4_K_M.gguf", | |
| "mmproj": "none", | |
| "n_ctx": 16384, | |
| "type": "lumina2" | |
| } | |
| }, | |
| "4": { | |
| "class_type": "DualHeadRewrite", | |
| "inputs": { | |
| "clip": [ | |
| "3", | |
| 0 | |
| ], | |
| "prompt": [ | |
| "1", | |
| 1 | |
| ], | |
| "system_prompt": "none", | |
| "system_prompt_text": [ | |
| "2", | |
| 0 | |
| ], | |
| "rewrite_lora": "zeng-v6_master-pe_lora_v4.1-r32-ep2_20260928-ck1212-qwen3vl-f16.gguf", | |
| "lora_strength": 1.0, | |
| "seed": 42, | |
| "max_new_tokens": 2048, | |
| "temperature": 0.7, | |
| "top_p": 0.8, | |
| "top_k": 20, | |
| "thinking": false, | |
| "draft": "zeng-v6_master-pe_dflash2_v4.1-b16-gen5_20260930-vocab16k-Q4_K_M.gguf", | |
| "draft_n_max": 15, | |
| "draft_tree": 20 | |
| } | |
| }, | |
| "5": { | |
| "class_type": "MasterStyleFinalize", | |
| "inputs": { | |
| "rewritten_prompt": [ | |
| "4", | |
| 0 | |
| ], | |
| "prompt": "A woman holding a lace parasol walking through a summer meadow", | |
| "style": "莫內印象光色 (monet_style)", | |
| "layout": "none", | |
| "wh_ratio": [ | |
| "4", | |
| 1 | |
| ], | |
| "megapixels_x100": 100 | |
| } | |
| }, | |
| "6": { | |
| "class_type": "CLIPLoader", | |
| "_meta": { | |
| "title": "FLUX.3 Klein text encoder (native, type flux3)" | |
| }, | |
| "inputs": { | |
| "clip_name": "flux3-klein-te-heretic-bf16.safetensors", | |
| "type": "flux3", | |
| "device": "default" | |
| } | |
| }, | |
| "7": { | |
| "class_type": "CLIPTextEncode", | |
| "inputs": { | |
| "clip": [ | |
| "6", | |
| 0 | |
| ], | |
| "text": [ | |
| "5", | |
| 0 | |
| ] | |
| } | |
| }, | |
| "8": { | |
| "class_type": "CLIPTextEncode", | |
| "inputs": { | |
| "clip": [ | |
| "6", | |
| 0 | |
| ], | |
| "text": "" | |
| } | |
| }, | |
| "9": { | |
| "class_type": "UNETLoader", | |
| "inputs": { | |
| "unet_name": "flux3-image-klein-nvfp4.safetensors", | |
| "weight_dtype": "default" | |
| } | |
| }, | |
| "10": { | |
| "class_type": "EmptyFlux2LatentImage", | |
| "inputs": { | |
| "width": [ | |
| "5", | |
| 1 | |
| ], | |
| "height": [ | |
| "5", | |
| 2 | |
| ], | |
| "batch_size": 1 | |
| } | |
| }, | |
| "11": { | |
| "class_type": "KSampler", | |
| "inputs": { | |
| "model": [ | |
| "9", | |
| 0 | |
| ], | |
| "positive": [ | |
| "7", | |
| 0 | |
| ], | |
| "negative": [ | |
| "8", | |
| 0 | |
| ], | |
| "latent_image": [ | |
| "10", | |
| 0 | |
| ], | |
| "seed": 42, | |
| "steps": 15, | |
| "cfg": 1.0, | |
| "sampler_name": "er_sde", | |
| "scheduler": "simple", | |
| "denoise": 1.0 | |
| } | |
| }, | |
| "12": { | |
| "class_type": "VAELoader", | |
| "inputs": { | |
| "vae_name": "flux2-vae.safetensors" | |
| } | |
| }, | |
| "13": { | |
| "class_type": "VAEDecode", | |
| "inputs": { | |
| "samples": [ | |
| "11", | |
| 0 | |
| ], | |
| "vae": [ | |
| "12", | |
| 0 | |
| ] | |
| } | |
| }, | |
| "14": { | |
| "class_type": "SaveImage", | |
| "inputs": { | |
| "images": [ | |
| "13", | |
| 0 | |
| ], | |
| "filename_prefix": "flux3_klein_master" | |
| } | |
| } | |
| } |