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

BeardedMonster
/
SabiBERTa-135M

Fill-Mask
Transformers
Safetensors
modernbert
african-languages
masked-lm
low-resource
sabiyarn
Model card Files Files and versions
xet
Community

Instructions to use BeardedMonster/SabiBERTa-135M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BeardedMonster/SabiBERTa-135M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="BeardedMonster/SabiBERTa-135M")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("BeardedMonster/SabiBERTa-135M")
    model = AutoModelForMaskedLM.from_pretrained("BeardedMonster/SabiBERTa-135M", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
SabiBERTa-135M
275 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 46 commits
BeardedMonster's picture
BeardedMonster
step 153218, loss_ema 1.4867, 40.17B tokens
359c1c3 verified 3 days ago
  • .gitattributes
    1.52 kB
    initial commit 6 days ago
  • README.md
    3.99 kB
    step 153218, loss_ema 1.4867, 40.17B tokens 3 days ago
  • config.json
    1.54 kB
    step 2000, loss_ema 3.1964, 0.52B tokens 6 days ago
  • model.safetensors
    272 MB
    xet
    step 153218, loss_ema 1.4867, 40.17B tokens 3 days ago
  • special_tokens_map.json
    162 Bytes
    tokenizer: <mask>=8 <cls>=11 <sep>=34, vocab 65,536 (audio slots repurposed) 6 days ago
  • tokenizer.json
    2.64 MB
    tokenizer: <mask>=8 <cls>=11 <sep>=34, vocab 65,536 (audio slots repurposed) 6 days ago
  • tokenizer_config.json
    276 Bytes
    tokenizer: <mask>=8 <cls>=11 <sep>=34, vocab 65,536 (audio slots repurposed) 6 days ago
  • training_state.json
    81 Bytes
    step 153218, loss_ema 1.4867, 40.17B tokens 3 days ago