Instructions to use amn-raw/gemma4-e4b-intent-tagging-v1-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use amn-raw/gemma4-e4b-intent-tagging-v1-merged with Transformers:

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

pipe = pipeline("automatic-speech-recognition", model="amn-raw/gemma4-e4b-intent-tagging-v1-merged")

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("amn-raw/gemma4-e4b-intent-tagging-v1-merged")
model = AutoModelForMultimodalLM.from_pretrained("amn-raw/gemma4-e4b-intent-tagging-v1-merged")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use amn-raw/gemma4-e4b-intent-tagging-v1-merged 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 amn-raw/gemma4-e4b-intent-tagging-v1-merged 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 amn-raw/gemma4-e4b-intent-tagging-v1-merged to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for amn-raw/gemma4-e4b-intent-tagging-v1-merged to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="amn-raw/gemma4-e4b-intent-tagging-v1-merged",
    max_seq_length=2048,
)

gemma4-e4b-intent-tagging-v1-merged / tokenizer.json

Commit History

(Trained with Unsloth)

18c7321
verified

amn-raw commited on 15 days ago

Commit History

(Trained with Unsloth) 18c7321 verified

(Trained with Unsloth)

18c7321
verified