Instructions to use Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX 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("Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX")

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 Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX"

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": "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX 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 "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX"

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 Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX"

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 "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX" \
  --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"

Pomona Nutrient / pH-EC Reasoner v0.1.1 MLX 8-bit

Experimental runtime artifact. Prepared locally only; not uploaded. This MLX package is an 8-bit conversion of the merged Pomona Nutrient/pH-EC v0.1.1 correction model, based on Qwen/Qwen2.5-0.5B-Instruct.

The source PEFT adapter passed its independent 140-case semantic evaluation with valid JSON, allowed labels/actions, nutrient label F1, blocked-action F1, and human-review match all at 1.0000. Conversion quality must be measured separately.

Runtime Evaluation

The MLX conversion passed a five-case smoke test for valid JSON, required fields, allowed values, blocked-action F1, and human-review match. Its nutrient label F1 was 0.8667, so it is not release-ready and has not passed the full 140-case holdout. Do not treat this package as equivalent to the source LoRA.

The Pomona guarded hybrid path applies deterministic rules after model generation. With that guard enabled, the same 140-case holdout reached valid JSON, allowed labels/actions, nutrient label F1, blocked-action F1, and human-review match of 1.0000 in every category. This measures the complete Pomona deployment path, not standalone MLX reasoning.

Scope And Safety

This is a narrow structured-output advisory reasoner for pH and EC telemetry. It must not change fertigation, inject nutrients, dose chemicals, control actuators, or provide a definitive disease diagnosis. Keep it behind Pomona's deterministic nutrient validation, safety checker, and human approval workflow.

Local Use

Serve locally with MLX-LM:

mlx_lm.server --model pomona-nutrient-ph-ec-reasoner-v0.1.1-8bit --port 8083

Use the exact training prompt and deterministic validation. The package is intended for local Apple Silicon experimentation until a full independent runtime evaluation passes.

For the guarded path, use scripts/models/guard_nutrient_ph_ec_output.py or the Pomona model-router deterministic route. guarded_evaluation.json records the guarded result; evaluation.json records the unguarded model-only result.

Related Projects

Platform and deterministic route: okyanu/pomona
Base model: Qwen/Qwen2.5-0.5B-Instruct
Source LoRA: pomona-nutrient-ph-ec-reasoner-v0.1.1-correction-lora

Downloads last month: 10

Safetensors

Model size

0.1B params

Tensor type

BF16

U32

MLX

Hardware compatibility

8-bit

Model tree for Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX

Base model

Qwen/Qwen2.5-0.5B

Finetuned

Qwen/Qwen2.5-0.5B-Instruct

Adapter

Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-lora

Quantized

(2)

this model

Okyanus
/

pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX

Pomona Nutrient / pH-EC Reasoner v0.1.1 MLX 8-bit

Runtime Evaluation

Scope And Safety

Local Use

Related Projects

Model tree for Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX

Dataset used to train Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-MLX