Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

google
/
gemma-4-E2B-it-qat-mobile-transformers

Any-to-Any
Transformers
Safetensors
gemma4
8-bit precision
gemma
Model card Files Files and versions
xet
Community
7

Instructions to use google/gemma-4-E2B-it-qat-mobile-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use google/gemma-4-E2B-it-qat-mobile-transformers with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("google/gemma-4-E2B-it-qat-mobile-transformers", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

what is the performance gap of this model with the full precision model?

#7 opened 10 days ago by
yuimo

How do we use MTP for speculative decoding?

1
#6 opened 23 days ago by
pythiccoder

Raise per-image vision soft-token budget from 280 to 1120

#2 opened 30 days ago by
lucianommartins
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs