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
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

hamingsi
/
SpikingLM

Fill-Mask
Transformers
Safetensors
PyTorch
bert
spiking-neural-network
masked-language-modeling
Model card Files Files and versions
xet
Community

Instructions to use hamingsi/SpikingLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hamingsi/SpikingLM with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="hamingsi/SpikingLM")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("hamingsi/SpikingLM")
    model = AutoModelForMaskedLM.from_pretrained("hamingsi/SpikingLM")
  • Notebooks
  • Google Colab
  • Kaggle
SpikingLM / spiking_bert
81 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
hamingsi's picture
hamingsi
Upload SpikingLM checkpoint and code
a9b7c0d verified 25 days ago
  • __init__.py
    254 Bytes
    Upload SpikingLM checkpoint and code 25 days ago
  • modeling_spiking_bert.py
    80.7 kB
    Upload SpikingLM checkpoint and code 25 days ago