Text Generation
Transformers
Safetensors
GGUF
English
qwen3_5
image-text-to-text
reasoning
hypnos
quantum-resonance
ibm-quantum
merlin-research
conversational
Eval Results
Instructions to use squ11z1/Hypnos-Q1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use squ11z1/Hypnos-Q1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="squ11z1/Hypnos-Q1") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("squ11z1/Hypnos-Q1") model = AutoModelForImageTextToText.from_pretrained("squ11z1/Hypnos-Q1") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - llama-cpp-python
How to use squ11z1/Hypnos-Q1 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="squ11z1/Hypnos-Q1", filename="Hypnos-Q1.F16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use squ11z1/Hypnos-Q1 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf squ11z1/Hypnos-Q1:Q4_K_M # Run inference directly in the terminal: llama-cli -hf squ11z1/Hypnos-Q1:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf squ11z1/Hypnos-Q1:Q4_K_M # Run inference directly in the terminal: llama-cli -hf squ11z1/Hypnos-Q1:Q4_K_M
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 squ11z1/Hypnos-Q1:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf squ11z1/Hypnos-Q1:Q4_K_M
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 squ11z1/Hypnos-Q1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf squ11z1/Hypnos-Q1:Q4_K_M
Use Docker
docker model run hf.co/squ11z1/Hypnos-Q1:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use squ11z1/Hypnos-Q1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "squ11z1/Hypnos-Q1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "squ11z1/Hypnos-Q1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/squ11z1/Hypnos-Q1:Q4_K_M
- SGLang
How to use squ11z1/Hypnos-Q1 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 "squ11z1/Hypnos-Q1" \ --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": "squ11z1/Hypnos-Q1", "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 "squ11z1/Hypnos-Q1" \ --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": "squ11z1/Hypnos-Q1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use squ11z1/Hypnos-Q1 with Ollama:
ollama run hf.co/squ11z1/Hypnos-Q1:Q4_K_M
- Unsloth Studio
How to use squ11z1/Hypnos-Q1 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 squ11z1/Hypnos-Q1 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 squ11z1/Hypnos-Q1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for squ11z1/Hypnos-Q1 to start chatting
- Pi
How to use squ11z1/Hypnos-Q1 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf squ11z1/Hypnos-Q1:Q4_K_M
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": "squ11z1/Hypnos-Q1:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use squ11z1/Hypnos-Q1 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf squ11z1/Hypnos-Q1: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 squ11z1/Hypnos-Q1:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use squ11z1/Hypnos-Q1 with Docker Model Runner:
docker model run hf.co/squ11z1/Hypnos-Q1:Q4_K_M
- Lemonade
How to use squ11z1/Hypnos-Q1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull squ11z1/Hypnos-Q1:Q4_K_M
Run and chat with the model
lemonade run user.Hypnos-Q1-Q4_K_M
List all available models
lemonade list
| { | |
| "backend": "ibm_kingston", | |
| "job_id": "d853tcvtjchs73bqs890", | |
| "n_qubits": 4, | |
| "shots_per_circuit": 1024, | |
| "corpus_size": 64, | |
| "signature_dim": 6, | |
| "signatures_sha256": "77097900d634c77fa0928d7766da49a113e8dddeb0e73b308d88b11437995409", | |
| "derived_seed": 8577520009804564351, | |
| "collection_seconds": 136.12, | |
| "timestamp_utc": "2026-05-17T22:20:59Z", | |
| "signatures_first_3": [ | |
| [ | |
| 0.31839999556541443, | |
| 0.26759999990463257, | |
| 0.6211000084877014, | |
| 0.05079999938607216, | |
| 0.35350000858306885, | |
| 0.302700012922287 | |
| ], | |
| [ | |
| -0.3319999873638153, | |
| -0.6445000171661377, | |
| -0.7383000254631042, | |
| 0.3125, | |
| 0.09380000084638596, | |
| 0.40619999170303345 | |
| ], | |
| [ | |
| 0.5917999744415283, | |
| -0.3984000086784363, | |
| -0.5898000001907349, | |
| 0.9901999831199646, | |
| 0.19140000641345978, | |
| 1.1815999746322632 | |
| ] | |
| ], | |
| "training_minutes": 65.12, | |
| "final_train_loss": 1.41, | |
| "training_samples": 8000 | |
| } |