Automatic Speech Recognition
Transformers
Safetensors
English
gemma4
image-text-to-text
text-generation-inference
unsloth
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
- Transformers
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, )
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