Feature Extraction
Transformers
Safetensors
English
Azerbaijani
modernbert
multilingual
vocabulary-truncation
encoder
fill-mask
azerbaijani
english
text-embeddings-inference
Instructions to use LocalDoc/mmBERT-small-en-az with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalDoc/mmBERT-small-en-az with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LocalDoc/mmBERT-small-en-az")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LocalDoc/mmBERT-small-en-az") model = AutoModel.from_pretrained("LocalDoc/mmBERT-small-en-az") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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| Vocabulary size | 256,000 | 71,751 |
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| Total parameters | 140.493M | 69.42M |
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| Embedding parameters |
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| Model size (fp32) | 0.52 GB | 0.26 GB |
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| Hidden size | 384 | 384 |
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| Layers | 22 | 22 |
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| Vocabulary size | 256,000 | 71,751 |
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| Total parameters | 140.493M | 69.42M |
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| Embedding parameters | 98.3M | 27.6M |
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| Model size (fp32) | 0.52 GB | 0.26 GB |
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| Hidden size | 384 | 384 |
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| Layers | 22 | 22 |
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