Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
german
nli
text-classification
text-embeddings-inference
Instructions to use airnicco8/xlm-roberta-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use airnicco8/xlm-roberta-de with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("airnicco8/xlm-roberta-de") 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 airnicco8/xlm-roberta-de with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("airnicco8/xlm-roberta-de") model = AutoModel.from_pretrained("airnicco8/xlm-roberta-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d98597d26857dd66f7ea5fe8362df32e55b6510833381e5c193bfbaf1d7ded60
- Size of remote file:
- 1.11 GB
- SHA256:
- 282c93cbec9b3b13bd3f5c1bdb4c63446da5ee67f1e6a2457708940e86da917c
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