Feature Extraction
sentence-transformers
Safetensors
Transformers
multilingual
qwen3
text-generation
custom_code
text-embeddings-inference
Instructions to use voyageai/voyage-4-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use voyageai/voyage-4-nano with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("voyageai/voyage-4-nano", trust_remote_code=True) 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] - Transformers
How to use voyageai/voyage-4-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="voyageai/voyage-4-nano", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("voyageai/voyage-4-nano", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("voyageai/voyage-4-nano", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
framework support via use_bidirectional_attention - Cheers from your friends at Baseten (#3)
Browse files- Cheers from your friends at Baseten (f6406a97f4824f6d25276a328c4fb8d259015528)
Co-authored-by: Michael <michaelfeil@users.noreply.huggingface.co>
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config.json
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"transformers_version": "4.51.3",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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"transformers_version": "4.51.3",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936,
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"use_bidirectional_attention": true
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}
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