metadata
language:
- en
license: apache-2.0
tags:
- text-generation
- instruct
- manim
- lora
- gguf
datasets:
- ArunKr/verified-data-manim
base_model: HuggingFaceTB/SmolLM-135M-Instruct
library_name: transformers
pipeline_tag: text-generation
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