---

license: apache-2.0

library_name: transformers

pipeline_tag: text-generation

base_model: Okyanus/pomona-water-irrigation-risk-reasoner-v0.1.8-lora

base_model_relation: quantized

tags:

- agriculture

- irrigation

- water-risk

- structured-output

- gguf

- ollama

- qwen2

- pomona

---

Pomona Water/Irrigation Risk Reasoner v0.1.8 GGUF

This repository contains the F16 GGUF deployment build of

Okyanus/pomona-water-irrigation-risk-reasoner-v0.1.8-lora.

It is a compact, narrow agricultural classifier derived from

Qwen/Qwen2.5-0.5B-Instruct and trained to return structured JSON for moisture

and irrigation-risk triage.

This is a deployment format, not a separately trained model. The LoRA

repository remains the canonical training artifact.

Intended Use

Given farm context, expected moisture fields, and sensor telemetry, the model

classifies:

• missing moisture;
• low/high moisture;
• under/overwatering risk;
• stale irrigation telemetry;
• impossible sensor values;
• insufficient context.

It also returns missing/suspect fields, safe manual checks, blocked action

classes, a human-review flag, and a short rationale.

Local Evaluation

The F16 GGUF build was evaluated locally against the same frozen independent

168-case holdout used for deployment acceptance, with 24 cases in each of

seven categories.

| Metric | Result |

|---|---:|

| Valid JSON | 1.0000 |

| Required fields present | 1.0000 |

| Allowed labels | 1.0000 |

| Allowed blocked actions | 1.0000 |

| Label F1 | 1.0000 |

| Blocked-action F1 | 1.0000 |

| Human-review match | 1.0000 |

| Evaluation time | 97.14 seconds |

The holdout is synthetic/rule-derived and checks the published task contract.

These results do not establish field validation, agronomic universality, or

safe autonomous control.

Ollama

Download the GGUF file and create a Modelfile:

FROM ./pomona-water-irrigation-v0.1.8-f16.gguf
PARAMETER temperature 0
PARAMETER num_predict 256

ollama create pomona-water-irrigation:v0.1.8 -f Modelfile
ollama run pomona-water-irrigation:v0.1.8

For reliable structured output, use the task prompt and validation contract in

the Pomona repository. Pomona's model

router validates allowed labels and combines model output with deterministic

rules.

Safety

This model is advisory only.

• Never connect it directly to pumps, valves, dosing equipment, or schedules.
• Never treat its output as a definitive crop or equipment diagnosis.
• Verify sensor readings and thresholds for the specific farm and substrate.
• Require human review for non-empty risk labels.
• Keep deterministic validation and the Pomona safety checker as final authority.

Lineage

Qwen/Qwen2.5-0.5B-Instruct
  -> Pomona Water/Irrigation Risk Reasoner v0.1.8 LoRA
    -> merged F16 model
      -> this GGUF deployment build

Related artifacts:

• Canonical LoRA adapter
• MLX 8-bit deployment
• Pomona platform

Limitations

• The model performs a narrow schema-bound classification task, not general agronomy.
• Thresholds must be calibrated for local systems and sensor units.
• Evaluation data is compact and rule-derived rather than a field deployment trial.
• Prompt, tokenizer, runtime, or quantization changes require fresh evaluation.
• Output wording may vary even when labels and safety decisions are correct.

License

Apache-2.0. See LICENSE.