Sentence Similarity
sentence-transformers
PyTorch
Transformers
roberta
feature-extraction
text-embeddings-inference
Instructions to use api19750904/newspainclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use api19750904/newspainclass with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("api19750904/newspainclass") 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 api19750904/newspainclass with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("api19750904/newspainclass") model = AutoModel.from_pretrained("api19750904/newspainclass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42eeb6d7bd97db896aa78d3cd37e553d705bb93b1856badcd7432cc2cc2892b2
- Size of remote file:
- 93.4 kB
- SHA256:
- 55b3981460194adc974803e0fc70567fff1403880e8a3bb0fa2fccbaf26b4e1a
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