Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:262023
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use dpshade22/hf-e5-bible-150 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dpshade22/hf-e5-bible-150 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dpshade22/hf-e5-bible-150") sentences = [ "query: Ezekiel Prophecies of Ezekiel", "passage: Then he went to the east gate. He climbed its steps and measured the threshold of the gate; it was one rod deep.", "passage: But if you do not obey the Lord, and if you rebel against his commands, his hand will be against you, as it was against your ancestors.", "passage: When you were dead in your sins and in the uncircumcision of your flesh, God made you alive with Christ. He forgave us all our sins," ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from dpshade22/hf-e5-bible-150: direct link, hf CLI and curl.
- Browser
- Download file 312 Bytes
-
https://huggingface.co/dpshade22/hf-e5-bible-150/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://dpshade22/hf-e5-bible-150/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/dpshade22/hf-e5-bible-150/resolve/main/1_Pooling/config.json
312 Bytes
| { | |
| "word_embedding_dimension": 768, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } |