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dhairyapandya/pathos-gemma4-distilled-rl-4B-GGUF overview

PathOS — Distilled GGUF for Ollama AI pathologist that runs offline on any laptop via Ollama. You can use this model locally on your computer through Ollama ht…

ggufhistopathologypathologymedicalgemma4ollamaendataset:wisdomik/QUILT-LLaVA-Instruct-107Klicense:cc-by-4.0endpoints_compatibleregion:usconversational

Runs locally from ~3.19 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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pathos-Q4_K_M.ggufGGUFQ4_K_M3.19 GBDownload

Model Details

Model IDdhairyapandya/pathos-gemma4-distilled-rl-4B-GGUF
Authordhairyapandya
Pipeline
Licensecc-by-4.0
Base modelgoogle/gemma-4-e2b-it
Last modified2026-08-24T20:39:20.000Z

Model README

---

language: en

license: cc-by-4.0

tags:

  • histopathology
  • pathology
  • medical
  • gemma4
  • gguf
  • ollama

base_model: google/gemma-4-e2b-it

datasets:

  • wisdomik/QUILT-LLaVA-Instruct-107K

---

PathOS — Distilled GGUF for Ollama

> AI pathologist that runs offline on any laptop via Ollama.

You can use this model locally on your computer through Ollama - https://ollama.com/dhairyapandya/pathos

Quick Start

# 1. Download pathos-Q4_K_M.gguf and Modelfile from this repo
# 2. Place both files in the same folder, then:
ollama create pathos -f Modelfile
ollama run pathos "Is malignancy present?"

Model Details

| Property | Value |

|---|---|

| Base model | Gemma 4 E2B (2.6B params) |

| Training | SFT + GRPO distillation |

| Quantization | Q4_K_M |

| Source | dhairyapandya/pathos-gemma4-distilled-rl-histopathology |

Distilled Techniques

All 6 inference-time techniques baked into the weights:

  1. Constrained decoding — always produces <answer> tags
  2. Anti-hedging — never says "cannot determine"
  3. Static RAG — few-shot exemplars in system prompt
  4. CoT routing — adapts reasoning to question type
  5. Per-type templates — YN/tissue/open formats
  6. Format compliance — GRPO reward shaping

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