How to use from
OpenClaw
Start the MLX server
# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mradermacher/soulbox-cbt-therapy-0.5b-GGUF"
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 "mradermacher/soulbox-cbt-therapy-0.5b-GGUF" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Quick Links

About

static quants of https://huggingface.co/kakashi3lite/soulbox-cbt-therapy-0.5b

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q3_K_S 0.4
GGUF Q2_K 0.4
GGUF IQ4_XS 0.5
GGUF Q3_K_M 0.5 lower quality
GGUF Q3_K_L 0.5
GGUF Q4_K_S 0.5 fast, recommended
GGUF Q4_K_M 0.5 fast, recommended
GGUF Q5_K_S 0.5
GGUF Q5_K_M 0.5
GGUF Q6_K 0.6 very good quality
GGUF Q8_0 0.6 fast, best quality
GGUF f16 1.1 16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

Downloads last month
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GGUF
Model size
0.5B params
Architecture
qwen2
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