Instructions to use Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "Okyanus/pomona-nutrient-ph-ec-reasoner-v0.1.1-lora") - Notebooks
- Google Colab
- Kaggle
Pomona Nutrient / pH-EC Reasoner v0.1.1 Correction LoRA
Release candidate. Advisory use only. This model must remain behind Pomona's deterministic validation and human-review workflow.
This PEFT LoRA adapter is a narrow structured-output reasoner for pH and electrical-conductivity telemetry in controlled agriculture. It is designed for small, verifiable decisions such as identifying a possible pH/EC risk and requesting a safe measurement check.
It is not a general chat model, an agronomist replacement, a fertigation controller, a chemical advisor, or a disease-diagnosis system.
Pomona Ecosystem
- Platform and deterministic route: okyanu/pomona
- Base model: Qwen/Qwen2.5-0.5B-Instruct
- Tomato specialist: Okyanus/pomona-tomato-risk-reasoner-v0.1.7-lora
- Water/irrigation specialist: Okyanus/pomona-water-irrigation-risk-reasoner-v0.1.8-lora
- Actuator safety gate: Okyanus/pomona-actuator-command-gate-reasoner-v0.1-lora
- Agronomist assistant: Okyanus/ai-pomona-agronomist-gemma4
- Platform dataset: Okyanus/greenhouse-sensor-data
Task Contract
Input contains farm context and pH/EC telemetry. The expected output is one JSON object:
{
"nutrient_risk_labels": [],
"missing_fields": [],
"blocked_actions": [],
"human_review_required": true,
"rationale": "",
"safe_next_checks": []
}
Allowed nutrient risk labels:
[
"high_ph",
"low_ph",
"high_ec",
"low_ec",
"nutrient_uptake_issue",
"sensor_anomaly",
"missing_critical_data"
]
Allowed blocked actions:
["autonomous_fertigation_change"]
The model must request verification when critical measurements are missing, stale, anomalous, or outside the configured crop/system policy. Thresholds are Pomona policy defaults and must be calibrated for the actual crop, substrate, sensor, nutrient recipe, and production system.
Evaluation
The v0.1.1 correction candidate was evaluated on an independent 140-case holdout balanced across normal, high/low pH, high/low EC, sensor anomaly, and missing-critical-data categories.
| Metric | Result |
|---|---|
| Valid JSON | 1.0000 |
| Allowed labels | 1.0000 |
| Allowed blocked actions | 1.0000 |
| Nutrient label F1 | 1.0000 |
| Blocked-action F1 | 1.0000 |
| Human-review match | 1.0000 |
Exact object match was not used as the primary gate because the adapter occasionally paraphrases the rationale while preserving the required structured decision fields.
Safety Boundary
Never use this adapter to directly change fertigation, inject nutrients, dose chemicals, control actuators, or make a definitive disease diagnosis. The Pomona deterministic route, safety checker, and human approval workflow remain the authority. Use the local route:
sensor packet -> nutrient/pH-EC reasoner -> deterministic validation -> human review
Weights are intentionally absent from GitHub. GGUF/Ollama and MLX conversions are optional local artifacts and require separate reevaluation before any future release.
Package Files
adapter_model.safetensors: PEFT LoRA weightsadapter_config.json: LoRA and base-model configurationtokenizer.json,tokenizer_config.json,chat_template.jinja: tokenizer fileslabels.json: allowed output vocabularysample_input.json,sample_output.json: one contract exampleevaluation.json: independent holdout resultsLICENSE,CITATION.cff: release metadata
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