Instructions to use zjsfxpm1/test-tags with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zjsfxpm1/test-tags with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zjsfxpm1/test-tags") 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 zjsfxpm1/test-tags with Transformers:
# Load model directly from transformers import TFAutoModel model = TFAutoModel.from_pretrained("zjsfxpm1/test-tags", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f3b0b7400aa20f76f1dcbd55199716941ae9b6d6b4288ea7f1064d73057c983
- Size of remote file:
- 153 MB
- SHA256:
- 6044a552e82c63230e4113f1cc247df0f075f5c8b400129d2db8b40d4fcd284b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.