Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
MT Evaluation
Metrics
Evaluation
text-embeddings-inference
Instructions to use AnanyaCoder/XLsim_en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AnanyaCoder/XLsim_en-de with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AnanyaCoder/XLsim_en-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 AnanyaCoder/XLsim_en-de with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnanyaCoder/XLsim_en-de") model = AutoModel.from_pretrained("AnanyaCoder/XLsim_en-de") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc7e49dcb3dc0a97099932bb5ec75cd395b819d0dee02c0778284bc0b61b0b24
- Size of remote file:
- 1.11 GB
- SHA256:
- d406f45acb4b8c78c8a18d6923a133f6e7a456decfe7e49e0ca9aef2646d6004
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