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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded finetuned model
- Developed by: amn-raw
- License: apache-2.0
- Finetuned from model : unsloth/gemma-4-E4B-it
This gemma4 model was trained 2x faster with Unsloth and Huggingface's TRL library.
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