---

license: apache-2.0

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

base_model_relation: quantized

datasets:

- Okyanus/greenhouse-sensor-data

library_name: llama.cpp

pipeline_tag: text-generation

tags:

- pomona

- agriculture

- nutrient-management

- ph

- ec

- gguf

- ollama

- small-reasoner

---

Pomona Nutrient / pH-EC Reasoner v0.1.1 GGUF

Experimental runtime artifact. Prepared locally only; not uploaded. This F16 GGUF is a conversion of the

Pomona Nutrient/pH-EC v0.1.1 correction LoRA merged into

Qwen/Qwen2.5-0.5B-Instruct.

The source adapter's independent 140-case semantic evaluation passed valid

JSON, allowed labels/actions, nutrient label F1, blocked-action F1, and

human-review match at 1.0. The conversion was evaluated with the exact

training prompt on the same 140-case holdout, but is not release-ready:

valid JSON and schema compliance were 1.0000, allowed-label rate was

0.8571, nutrient-label F1 was 0.6690, blocked-action F1 was 0.8571, and

human-review match was 0.8571. Normal and missing-critical-data cases were

the main failures. These runtime results do not represent the quality of the

source PEFT adapter.

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 GGUF reasoning.

Use only as an advisory component behind Pomona's deterministic nutrient and

safety routes. Never use it to directly change fertigation, dose chemicals,

control actuators, or diagnose disease.

Local Ollama name prepared: pomona-nutrient-ph-ec:v0.1.1.

Related platform: okyanu/pomona

Usage

This is a raw GGUF model for llama.cpp-compatible runtimes. The local Ollama

wrapper used for testing was:

FROM pomona-nutrient-ph-ec-v0.1.1-f16.gguf
PARAMETER temperature 0
PARAMETER num_predict 220

Use the exact task prompt and keep deterministic validation in front of any

fertigation workflow. A prompt or runtime wrapper is not a substitute for the

deterministic Pomona safety route.

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.

Release Status

This package is structurally uploadable as an experimental conversion,

but it is not an approved production or release-candidate runtime. The

canonical PEFT LoRA remains the reference artifact until this conversion

passes an independent full holdout.