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

mosaicml
/
mosaic-bert-base-seqlen-1024

Fill-Mask
Transformers
PyTorch
English
bert
custom_code
Model card Files Files and versions
xet
Community
5

Instructions to use mosaicml/mosaic-bert-base-seqlen-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mosaicml/mosaic-bert-base-seqlen-1024 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="mosaicml/mosaic-bert-base-seqlen-1024", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("mosaicml/mosaic-bert-base-seqlen-1024", trust_remote_code=True)
    model = AutoModelForMaskedLM.from_pretrained("mosaicml/mosaic-bert-base-seqlen-1024", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
mosaic-bert-base-seqlen-1024
550 MB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 14 commits
daking's picture
daking
kobindra's picture
kobindra
Create LICENSE (#2)
b9fba86 verified about 2 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • LICENSE
    11.3 kB
    Create LICENSE (#2) about 2 years ago
  • README.md
    13.9 kB
    Update citation in README over 2 years ago
  • bert_layers.py
    47.3 kB
    Upload BertForMaskedLM about 3 years ago
  • bert_padding.py
    6.26 kB
    Upload BertForMaskedLM about 3 years ago
  • config.json
    845 Bytes
    Change attention_probs_dropout_prob to 0.1 so that triton FlashAttention dependencies are avoided over 2 years ago
  • configuration_bert.py
    1.01 kB
    Upload BertForMaskedLM about 3 years ago
  • flash_attn_triton.py
    42.7 kB
    Upload BertForMaskedLM about 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage"

    What is a pickle import?

    550 MB
    xet
    Upload BertForMaskedLM about 3 years ago