Sentence Similarity
sentence-transformers
Safetensors
bert
embedding
context-curation
long-context
memory-management
retrieval
text-embeddings-inference
Instructions to use SkyIsNotGreen/splinter-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SkyIsNotGreen/splinter-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SkyIsNotGreen/splinter-encoder") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 295 Bytes
7392b7f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"student": "sentence-transformers/paraphrase-MiniLM-L3-v2",
"teacher": "",
"examples": 561,
"epochs": 1,
"batch_size": 16,
"lr": 5e-06,
"temperature": 0.05,
"alpha": 0.5,
"hard_weight": 0.5,
"seed": 20261020,
"seconds": 82.5,
"history": [
{
"epoch": 0,
"steps": 35
}
]
} |