eastrus-vl-qwen3-2b-gguf

A GGUF-exported multimodal (vision-language) model based on Qwen3-VL-2B-Instruct, fine-tuned for cattle estrus–related vulval image assessment. The model is intended to produce symptom-by-symptom observations and a single confidence-style score, rather than a hard binary decision.

This repo contains:

• A quantized GGUF model for inference (Q4_K_M)
• A matching multimodal projection file (mmproj) required by llama.cpp for vision inputs

Model details

• Base model: Qwen3-VL-2B-Instruct (VLM)
• Fine-tuning: Unsloth (LoRA / efficient finetuning workflow)
• Export: llama.cpp GGUF conversion via Unsloth
• Quantization: Q4_K_M (balanced quality/speed)

Intended use

• Primary: Assistive analysis of cattle vulval imagery for estrus-related visual signs (educational/research workflow support).
• Not a medical device: Outputs should not be used as the sole basis for veterinary diagnosis, treatment, or critical farm management decisions.

Output format (what you should expect)

The model is trained to generate:

• A structured, human-readable symptom list (mucus color, swelling severity, redness severity, moisture level, mucus viscosity, tissue turgidity)
• A single confidence-style score (0–100%)
• A JSON structured summary of all observed symptoms

How to run (llama.cpp)

1) Text-only prompt (sanity check)

llama-cli -hf prapaa/eastrus-vl-qwen3-2b-gguf --jinja -p "Is there eastrus?"