Sentence Similarity
sentence-transformers
Safetensors
English
roberta
glyph
ape
embeddings
gguf-friendly
text-embeddings-inference
Instructions to use wimpSquad/glyph-embedder-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use wimpSquad/glyph-embedder-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("wimpSquad/glyph-embedder-v2") 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
| { | |
| "from_mlm": "/home/v/ape-v2-train/pretrain-run1/final", | |
| "triples_file": "/home/v/ape-v2-train/contrastive_train_v22.jsonl", | |
| "n_triples": 118817, | |
| "kind_counts": { | |
| "rename": 59347, | |
| "paraphrase": 59470 | |
| }, | |
| "epochs": 4, | |
| "batch_size": 128, | |
| "lr": 2e-05, | |
| "warmup": 200, | |
| "fp16": true | |
| } |