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alphaedge-ai
/
mt5-base-nep-16384

Fill-Mask
Transformers
Safetensors
Nepali (macrolanguage)
mt5
text2text-generation
trimmed
Model card Files Files and versions
xet
Community

Instructions to use alphaedge-ai/mt5-base-nep-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use alphaedge-ai/mt5-base-nep-16384 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="alphaedge-ai/mt5-base-nep-16384")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mt5-base-nep-16384")
    model = AutoModelForSeq2SeqLM.from_pretrained("alphaedge-ai/mt5-base-nep-16384")
  • Notebooks
  • Google Colab
  • Kaggle
mt5-base-nep-16384
894 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
lbourdois's picture
lbourdois
Update model card for Nepali
5d9f550 verified 10 days ago
  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    2.36 kB
    Update model card for Nepali 10 days ago
  • config.json
    727 Bytes
    Trimmed google/mt5-base for Nepali (16384 tokens) 3 months ago
  • generation_config.json
    153 Bytes
    Trimmed google/mt5-base for Nepali (16384 tokens) 3 months ago
  • model.safetensors
    894 MB
    xet
    Trimmed google/mt5-base for Nepali (16384 tokens) 3 months ago
  • special_tokens_map.json
    113 Bytes
    Trimmed google/mt5-base for Nepali (16384 tokens) 3 months ago
  • spiece.model
    494 kB
    xet
    Trimmed google/mt5-base for Nepali (16384 tokens) 3 months ago
  • tokenizer_config.json
    96 Bytes
    Trimmed google/mt5-base for Nepali (16384 tokens) 3 months ago