Instructions to use vincentoh/gemma3-27b-af-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use vincentoh/gemma3-27b-af-detector with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-27b-it-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "vincentoh/gemma3-27b-af-detector")

Transformers

How to use vincentoh/gemma3-27b-af-detector with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="vincentoh/gemma3-27b-af-detector")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("vincentoh/gemma3-27b-af-detector", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use vincentoh/gemma3-27b-af-detector with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for vincentoh/gemma3-27b-af-detector to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for vincentoh/gemma3-27b-af-detector to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for vincentoh/gemma3-27b-af-detector to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="vincentoh/gemma3-27b-af-detector",
    max_seq_length=2048,
)

gemma3-27b-af-detector / special_tokens_map.json

Commit History

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vincentoh commited on Jan 1

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