Sentence Similarity
sentence-transformers
Safetensors
Hausa
Yoruba
Igbo
modernbert
feature-extraction
nigerian
hausa
yoruba
igbo
cross-lingual
text-embeddings-inference
Instructions to use olaverse/naija-embed-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use olaverse/naija-embed-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("olaverse/naija-embed-base") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +51 -2
- tokenizer_config.json +5 -12
tokenizer.json
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"post_processor": {
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"type": "TemplateProcessing",
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"decoder": {
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"type": "ByteLevel",
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"decoder": {
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"type": "ByteLevel",
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tokenizer_config.json
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{
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"mask_token": "<mask>",
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"max_length": 128,
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"tokenizer_class": "TokenizersBackend",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "[UNK]"
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}
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