Text Generation
GGUF
Safetensors
English
qwen3
zero-loop
zero-labs
foundation-model
small-language-model
on-device
edge
tool-use
reasoning
llama.cpp
conversational
Instructions to use ZEROLABS1/zero-loop 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 ZEROLABS1/zero-loop 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 ZEROLABS1/zero-loop:Q4_K_M # Run inference directly in the terminal: llama cli -hf ZEROLABS1/zero-loop:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ZEROLABS1/zero-loop:Q4_K_M # Run inference directly in the terminal: llama cli -hf ZEROLABS1/zero-loop: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 ZEROLABS1/zero-loop:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf ZEROLABS1/zero-loop:Q4_K_M
Use Docker
docker model run hf.co/ZEROLABS1/zero-loop:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use ZEROLABS1/zero-loop with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ZEROLABS1/zero-loop" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZEROLABS1/zero-loop", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ZEROLABS1/zero-loop:Q4_K_M
- Ollama
How to use ZEROLABS1/zero-loop with Ollama:
ollama run hf.co/ZEROLABS1/zero-loop:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use ZEROLABS1/zero-loop with Docker Model Runner:
docker model run hf.co/ZEROLABS1/zero-loop:Q4_K_M
- Lemonade
How to use ZEROLABS1/zero-loop with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ZEROLABS1/zero-loop:Q4_K_M
Run and chat with the model
lemonade run user.zero-loop-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download base/config.json from ZEROLABS1/zero-loop: direct link, hf CLI and curl.
- Browser
- Download file 1.15 kB
-
https://huggingface.co/ZEROLABS1/zero-loop/resolve/main/base/config.json
- Command line
-
hf download hf://ZEROLABS1/zero-loop/base/config.json
-
curl -L -o config.json https://huggingface.co/ZEROLABS1/zero-loop/resolve/main/base/config.json
1.15 kB
| { | |
| "architectures": [ | |
| "Qwen3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": null, | |
| "dtype": "float32", | |
| "eos_token_id": 16379, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 256, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1024, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 4096, | |
| "max_window_layers": 28, | |
| "model_type": "qwen3", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 16, | |
| "num_key_value_heads": 2, | |
| "pad_token_id": 16374, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| }, | |
| "sliding_window": null, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.18.0", | |
| "use_cache": true, | |
| "use_sliding_window": false, | |
| "vocab_size": 16384 | |
| } | |