How to use from
Pi
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf eugenehp/qwen3-0.6b: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": "eugenehp/qwen3-0.6b:Q4_K_M"
        }
      ]
    }
  }
}
Run Pi
# Start Pi in your project directory:
pi
Quick Links

Qwen3-0.6B (RLX staging)

Qwen3-0.6B safetensors + tokenizer for RLX.

Field Value
Hub id eugenehp/qwen3-0.6b
Kind Staging redistrib of an upstream checkpoint for RLX runners.
RLX crate rlx-qwen3
Upstream https://huggingface.co/Qwen/Qwen3-0.6B

Quick start

hf download eugenehp/qwen3-0.6b --local-dir .
cargo run -p rlx-qwen3 --release -- --weights . --device metal

File highlights

  • model.safetensors (1.4 GiB)
  • Qwen3-0.6B-Q4_K_M.gguf (378.3 MiB)
  • tokenizer.json (10.9 MiB)
  • vocab.json (2.6 MiB)
  • merges.txt (1.6 MiB)
  • tokenizer_config.json (9.5 KiB)
  • config.json (726 B)
  • generation_config.json (239 B)

Run with RLX

Clone rlx-models, place this repo under weights/lm/qwen3-0.6b (or pass the path explicitly), then:

cargo run -p rlx-qwen3 --release -- --weights . --device metal

License

Apache License 2.0 — see LICENSE. Inherit upstream terms when redistributing.

Original weights and authorship: https://huggingface.co/Qwen/Qwen3-0.6B

Redistrib note

This Hub repo exists so RLX recipes have a stable fetch target. When you only need the upstream checkpoint, prefer the Upstream link above.

Downloads last month
92
Safetensors
Model size
0.8B params
Tensor type
BF16
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