Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers
Vietnamese
roberta
feature-extraction
phobert
vietnamese
sentence-embedding
Instructions to use dangvantuan/vietnamese-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dangvantuan/vietnamese-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dangvantuan/vietnamese-embedding") 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 dangvantuan/vietnamese-embedding with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dangvantuan/vietnamese-embedding") model = AutoModel.from_pretrained("dangvantuan/vietnamese-embedding", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding ONNX file of this model
Verified signatureBeep boop I am the [ONNX export bot 🤖🏎️](https://huggingface.co/spaces/onnx/export). On behalf of [haunn](https://huggingface.co/haunn), I would like to add to this repository the model converted to ONNX. What is ONNX? It stands for "Open Neural Network Exchange", and is the most commonly used open standard for machine learning interoperability. You can find out more at [onnx.ai](https://onnx.ai/)! The exported ONNX model can be then be consumed by various backends as TensorRT or TVM, or simply be used in a few lines with 🤗 Optimum through ONNX Runtime, check out how [here](https://huggingface.co/docs/optimum/main/en/onnxruntime/usage_guides/models)!65d85ce
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