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
Download generation_config.json from zeroentropy/zembed-1-embedding: direct link, hf CLI and curl.
- Browser
- Download file 214 Bytes
-
https://huggingface.co/zeroentropy/zembed-1-embedding/resolve/main/generation_config.json
- Command line
-
hf download hf://zeroentropy/zembed-1-embedding/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/zeroentropy/zembed-1-embedding/resolve/main/generation_config.json
214 Bytes
| { | |
| "bos_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "pad_token_id": 151643, | |
| "temperature": 0.6, | |
| "top_k": 20, | |
| "top_p": 0.95, | |
| "transformers_version": "4.57.1" | |
| } | |