ArunKr/gemma-3-270m-it-web-agent-gguf

gemma-3-270m-it-web-agent - Fine-tuned

This repository contains three variants of the model:

• LoRA adapters → ArunKr/gemma-3-270m-it-web-agent-lora
• Merged FP16 weights → ArunKr/gemma-3-270m-it-web-agent-16bit
• GGUF quantizations → ArunKr/gemma-3-270m-it-web-agent-gguf

Training

• Base model: unsloth/gemma-3-270m-it
• Dataset: ArunKr/gui_grounding_dataset-100
• Method: LoRA fine-tuning with Unsloth

Quantizations

We provide f16, bf16, f32, and q8_0 GGUF files for llama.cpp / Ollama.

Usage Example

from transformers import AutoModelForCausalLM, AutoTokenizer

tok = AutoTokenizer.from_pretrained("ArunKr/gemma-3-270m-it-web-agent-16bit")
model = AutoModelForCausalLM.from_pretrained("ArunKr/gemma-3-270m-it-web-agent-16bit")
print(model.generate(**tok("Hello", return_tensors="pt")))

Ollama Example

ollama run ArunKr/SmolLM-135M-Instruct-manim-gguf:<file_name>.gguf

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