Instructions to use FastFlowLM/Gemma4-E2B-IT-NPU2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FastFlowLM/Gemma4-E2B-IT-NPU2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("FastFlowLM/Gemma4-E2B-IT-NPU2") model = AutoModelForMultimodalLM.from_pretrained("FastFlowLM/Gemma4-E2B-IT-NPU2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Create README.md
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feat: Q8_0 embedding
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feat: add audio weights
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Update config.json (#1)
- Update config.json (23be7fff9eb4263d7634913c9cd7dca6469cad2f) Co-authored-by: Shouyu <Shouyu-joel@users.noreply.huggingface.co>f110044
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Update config.json
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feat: init_commit
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initial commit
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