Instructions to use witty-works/optim_false_positive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use witty-works/optim_false_positive with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("witty-works/optim_false_positive") 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 witty-works/optim_false_positive with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("witty-works/optim_false_positive") model = AutoModel.from_pretrained("witty-works/optim_false_positive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea60209fdd4f5f55aec4a2d633b49f4b74c38746d3d4144942d190352988e05b
- Size of remote file:
- 46.7 MB
- SHA256:
- 9b6ab03ae340d9f1c6089316ea466dfb37ad77d62c7fa0be4a30cf4ae4b015e5
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