Instructions to use jialinyyzz/humanizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jialinyyzz/humanizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jialinyyzz/humanizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("jialinyyzz/humanizer") model = AutoModelForMultimodalLM.from_pretrained("jialinyyzz/humanizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jialinyyzz/humanizer 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 jialinyyzz/humanizer:Q4_K_M # Run inference directly in the terminal: llama cli -hf jialinyyzz/humanizer:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jialinyyzz/humanizer:Q4_K_M # Run inference directly in the terminal: llama cli -hf jialinyyzz/humanizer: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 jialinyyzz/humanizer:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf jialinyyzz/humanizer:Q4_K_M
Use Docker
docker model run hf.co/jialinyyzz/humanizer:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use jialinyyzz/humanizer with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jialinyyzz/humanizer" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jialinyyzz/humanizer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jialinyyzz/humanizer:Q4_K_M
- SGLang
How to use jialinyyzz/humanizer with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "jialinyyzz/humanizer" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jialinyyzz/humanizer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "jialinyyzz/humanizer" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jialinyyzz/humanizer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use jialinyyzz/humanizer with Ollama:
ollama run hf.co/jialinyyzz/humanizer:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use jialinyyzz/humanizer with Docker Model Runner:
docker model run hf.co/jialinyyzz/humanizer:Q4_K_M
- Lemonade
How to use jialinyyzz/humanizer with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jialinyyzz/humanizer:Q4_K_M
Run and chat with the model
lemonade run user.humanizer-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Seems to work well with the original AI as "fact-checker".
I didn't try with any AI detectors. Sequence - original AI (e.g. GPT-6 Luna) -> humanizer -> original AI again
Sample business email
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You said
create a one-paragraph sample business email
Duck.ai said
Subject: Project Update
Hi Jordan, I’m writing to share a brief update on the project: we’ve completed the research phase and are on track to deliver the first draft by Friday. Please let me know if you’d like to review the outline beforehand or have any feedback to incorporate. Best, Taylor
You said
Thanks. Below is the output of another AI "humanizer" that took the above paragraph as the input. What is your opinion? Does it read more like a human wrote it? "Hey Jordan - just a quick project update. We are finished with our research, and will have the first draft done by Friday. Let me know if you want to see a rough outline ahead of time. Or if you have any feedback for us to include. Best, Taylor"
Duck.ai said
It sounds more casual and conversational, which can feel more human, but it’s a little less polished. “Or if you have any feedback for us to include” is a sentence fragment, and “rough outline” slightly changes the original meaning. I’d smooth it out: “Hey Jordan, just a quick project update: we’ve finished the research and expect to have the first draft ready by Friday. Let me know if you’d like to see the outline beforehand or have any feedback for us to incorporate. Best, Taylor.”
Nice workflow, thanks for sharing! That’s pretty much how I’d use it too: humanizer for the voice, then a quick pass with a strong model (or your own eyes) to catch fragments or small shifts like “outline” → “rough outline”. It’s tuned to keep names, dates and numbers, but it loosens wording on purpose, so a final read is a good idea for anything important.