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niranjanh123/gemma-video-captions-GGUF overview

gemma video captions GGUF : GGUF This model was finetuned and converted to GGUF format using Unsloth https://github.com/unslothai/unsloth . Example usage : For…

ggufgemma4llama.cppunslothvision-language-modelendpoints_compatibleregion:usconversational

Runs locally from ~941.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
gemma-4-e2b-it.BF16-mmproj.ggufGGUFGGUF941.1 MBDownload
gemma-4-e2b-it.Q4_K_M.ggufGGUFGGUF3.19 GBDownload

Model Details

Model IDniranjanh123/gemma-video-captions-GGUF
Authorniranjanh123
Pipeline
License
Base model
Last modified2026-07-12T17:36:47.000Z

Model README

---

tags:

  • gguf
  • llama.cpp
  • unsloth
  • vision-language-model

---

gemma-video-captions-GGUF : GGUF

This model was finetuned and converted to GGUF format using Unsloth.

Example usage:

  • For text only LLMs: llama-cli -hf niranjanh123/gemma-video-captions-GGUF --jinja
  • For multimodal models: llama-mtmd-cli -hf niranjanh123/gemma-video-captions-GGUF --jinja

Available Model files:

  • gemma-4-e2b-it.Q4_K_M.gguf
  • gemma-4-e2b-it.BF16-mmproj.gguf

⚠️ Ollama Note for Vision Models

Important: Ollama currently does not support separate mmproj files for vision models.

To create an Ollama model from this vision model:

  1. Place the Modelfile in the same directory as the finetuned bf16 merged model
  2. Run: ollama create model_name -f ./Modelfile

(Replace model_name with your desired name)

This will create a unified bf16 model that Ollama can use.

This was trained 2x faster with Unsloth

<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>

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