Feature Extraction
sentence-transformers
Safetensors
English
multilingual
qwen3
finance
legal
healthcare
code
stem
medical
text-embeddings-inference
Instructions to use zeroentropy/zembed-1-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zeroentropy/zembed-1-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zeroentropy/zembed-1-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] - Notebooks
- Google Colab
- Kaggle
Correct max_seq_length in sentence_bert_config.json
#4
by jacobmagnuson - opened
sentence_bert_config.json
CHANGED
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@@ -1,4 +1,4 @@
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{
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-
"max_seq_length":
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"do_lower_case": false
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}
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{
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+
"max_seq_length": 32768,
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"do_lower_case": false
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}
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