Feature Extraction
sentence-transformers
Safetensors
qwen3
sentence-similarity
text-embeddings
indic
multilingual
mteb
text-embeddings-inference
Instructions to use LingoIITGN/FlowVec-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LingoIITGN/FlowVec-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LingoIITGN/FlowVec-v1") 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
Download 2_Normalize/config.json from LingoIITGN/FlowVec-v1: direct link, hf CLI and curl.
- Browser
- Download file 2 Bytes
-
https://huggingface.co/LingoIITGN/FlowVec-v1/resolve/main/2_Normalize/config.json
- Command line
-
hf download hf://LingoIITGN/FlowVec-v1/2_Normalize/config.json
-
curl -L -o config.json https://huggingface.co/LingoIITGN/FlowVec-v1/resolve/main/2_Normalize/config.json
2 Bytes
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