# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("NtDNlp/sentence-embedding-vietnamese")
model = AutoModel.from_pretrained("NtDNlp/sentence-embedding-vietnamese")Quick Links
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Check out the documentation for more information.
#EmbeddingSimilarityEvaluator: Evaluating the model on STS.en-en.txt dataset in epoch 2 after 26000 steps:
| Type | Pearson | Spearman |
|---|---|---|
| Cosine | 0.7650 | 0.8095 |
| Euclidean | 0.8089 | 0.8010 |
| Cosine | 0.8075 | 0.7999 |
| Euclidean | 0.7531 | 0.7680 |
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="NtDNlp/sentence-embedding-vietnamese")