Instructions to use TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke"

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 TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke"

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 "TiGa-RCE/Bonsai-27B-oQ2e-S32-Smoke" \
  --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"

TiGa-RCE commited on Jul 27

Commit

cf9d7d7

verified ·

1 Parent(s): 9c3c725

Cross-link Bonsai MLX experiment family and runtime gate

Browse files

Files changed (1) hide show

README.md +18 -0

README.md CHANGED Viewed

@@ -21,6 +21,24 @@ base_model:
 > **Experimental calibration artifact. Not a quality release. Do not use this
 > model to judge Bonsai quality or as a production checkpoint.**
 This repository preserves the first bounded oQe 2-bit output that loaded and
 generated normally on a 32 GB Apple Silicon host. Its purpose is reproducible
 pipeline evidence and storage, not a recommended deployment target.

 > **Experimental calibration artifact. Not a quality release. Do not use this
 > model to judge Bonsai quality or as a production checkpoint.**
+## Experiment family and current status
+This is one public checkpoint in an **unfinished** MLX/oMLX compatibility and
+quantization experiment:
+- [BF16 config-repaired archival baseline](https://huggingface.co/TiGa-RCE/Bonsai-27B-MLX-BF16-Config-Repaired)
+- **oQ2e S32 calibration smoke — this repository**
+- [oQ4e S32 calibration smoke](https://huggingface.co/TiGa-RCE/Bonsai-27B-oQ4e-S32-Smoke)
+The experiment remains incomplete until maintained MLX/MLX-LM/oMLX support can
+load and generate through the relevant Bonsai paths without the current local
+compatibility patches, explicit calibration proxies, or imatrix-boundary
+workarounds. The larger predeclared evaluations follow that runtime gate.
+The Hub's approximately `3B` badge counts packed quantized storage tensors. It
+does not mean this is a newly trained 3B model; the logical source architecture
+is Bonsai 27B.
 This repository preserves the first bounded oQe 2-bit output that loaded and
 generated normally on a 32 GB Apple Silicon host. Its purpose is reproducible
 pipeline evidence and storage, not a recommended deployment target.