Sentence Similarity
sentence-transformers
Safetensors
t5
feature-extraction
Generated from Trainer
dataset_size:7106
loss:MultipleNegativesRankingLoss
Instructions to use KasuleTrevor/Sentence-t5-large-QQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use KasuleTrevor/Sentence-t5-large-QQ with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KasuleTrevor/Sentence-t5-large-QQ") sentences = [ "why should a farmer castrate his/her animals", "In what situations should farmers consider castrating their animals?", "How can I prevent annual parasite attacks on my chickens?", "In what ways can a farmer ascertain the viability of coffee berries?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download modules.json from KasuleTrevor/Sentence-t5-large-QQ: direct link, hf CLI and curl.
- Browser
- Download file 461 Bytes
-
https://huggingface.co/KasuleTrevor/Sentence-t5-large-QQ/resolve/main/modules.json
- Command line
-
hf download hf://KasuleTrevor/Sentence-t5-large-QQ/modules.json
-
curl -L -o modules.json https://huggingface.co/KasuleTrevor/Sentence-t5-large-QQ/resolve/main/modules.json
461 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Dense", | |
| "type": "sentence_transformers.models.Dense" | |
| }, | |
| { | |
| "idx": 3, | |
| "name": "3", | |
| "path": "3_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |