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miguelcsx
/
mosaic-memory-d384-bbpe16k

Fill-Mask
Transformers
Safetensors
English
tolm
small-language-model
developmental-language-modeling
strict-small
masked-language-modeling
data2vec
whole-word-masking
mosaic
custom_code
Model card Files Files and versions
xet
Community

Instructions to use miguelcsx/mosaic-memory-d384-bbpe16k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use miguelcsx/mosaic-memory-d384-bbpe16k with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="miguelcsx/mosaic-memory-d384-bbpe16k", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForMaskedLM
    model = AutoModelForMaskedLM.from_pretrained("miguelcsx/mosaic-memory-d384-bbpe16k", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
mosaic-memory-d384-bbpe16k
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  • 1 contributor
History: 5 commits
miguelcsx's picture
miguelcsx
docs: update repository provenance
885aee3 verified about 3 hours ago
  • .gitattributes
    1.52 kB
    initial commit about 3 hours ago
  • README.md
    4.62 kB
    docs: use MOSAIC public naming about 3 hours ago
  • config.json
    1.06 kB
    release: publish final 100M checkpoint about 3 hours ago
  • model.safetensors
    133 MB
    xet
    release: publish final 100M checkpoint about 3 hours ago
  • release_manifest.json
    14 kB
    docs: update repository provenance about 3 hours ago
  • special_tokens_map.json
    122 Bytes
    release: publish final 100M checkpoint about 3 hours ago
  • tokenizer.json
    1.12 MB
    release: publish final 100M checkpoint about 3 hours ago
  • tokenizer_config.json
    242 Bytes
    release: publish final 100M checkpoint about 3 hours ago
  • tolm.py
    23.8 kB
    release: publish final 100M checkpoint about 3 hours ago
  • training_manifest.json
    4.05 kB
    release: publish final 100M checkpoint about 3 hours ago