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)# pip install -U transformers accelerate # 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
Download config_sentence_transformers.json from voyageai/voyage-4-nano: direct link, hf CLI and curl.
- Browser
- Download file 378 Bytes
-
https://huggingface.co/voyageai/voyage-4-nano/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://voyageai/voyage-4-nano/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/voyageai/voyage-4-nano/resolve/main/config_sentence_transformers.json
378 Bytes
| { | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.0.0", | |
| "transformers": "4.51.3", | |
| "pytorch": "2.9.1+cu130" | |
| }, | |
| "prompts": { | |
| "query": "Represent the query for retrieving supporting documents: ", | |
| "document": "Represent the document for retrieval: " | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |