Feature Extraction
sentence-transformers
Safetensors
English
multilingual
qwen3
text-embeddings-inference
infinity
Instructions to use michaelfeil/zembed-1-infinity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use michaelfeil/zembed-1-infinity with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("michaelfeil/zembed-1-infinity") 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
File size: 656 Bytes
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"source": "zeroentropy/zembed-1-embedding",
"revision": "cf13c81f3274394053d166740294f7eea4586f7a",
"changes": {
"modules.json": "Replace ZembedTransformer with standard Transformer; client supplies original terminal suffix."
},
"required_input_suffix": "<|im_end|>\n",
"output_dimensions": 2560,
"weight_sha256": {
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