Feature Extraction
Transformers
PyTorch
TensorFlow
Safetensors
French
English
multilingual
xlm-roberta
sentence_embedding
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roberta
xlm-r-distilroberta-base-paraphrase-v1
Instructions to use T-Systems-onsite/cross-en-fr-roberta-sentence-transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use T-Systems-onsite/cross-en-fr-roberta-sentence-transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="T-Systems-onsite/cross-en-fr-roberta-sentence-transformer")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("T-Systems-onsite/cross-en-fr-roberta-sentence-transformer") model = AutoModel.from_pretrained("T-Systems-onsite/cross-en-fr-roberta-sentence-transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"eps": 4.462251033010287e-06, "lr": 1.026343323298136e-05, "num_epochs": 2, "train_batch_size": 8, "warmup_steps_mul": 0.1609010732760181, "weight_decay": 0.04794438776350409, "lang_1_test_result_spearman": 0.8652970299408306, "lang_2_test_result_spearman": 0.844267768829181, "lang_cross_test_result_spearman": 0.8456719879412349, "lang_all_test_result_spearman": 0.8494277454964172, "languages": ["en", "fr"]} |