Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use thtang/ALL_936309 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thtang/ALL_936309 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thtang/ALL_936309") 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] - Transformers
How to use thtang/ALL_936309 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("thtang/ALL_936309") model = AutoModel.from_pretrained("thtang/ALL_936309", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a6e365eb84af7b34d77a2f73d7129e0465465fa516621db303070ae08471bf3
- Size of remote file:
- 471 MB
- SHA256:
- c1b8c799408a1e88d5d63a692879e6e4aa8c67ec653079a02f0132b6f408b96e
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