Instructions to use T-Systems-onsite/cross-en-zh-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-zh-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-zh-roberta-sentence-transformer")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("T-Systems-onsite/cross-en-zh-roberta-sentence-transformer") model = AutoModel.from_pretrained("T-Systems-onsite/cross-en-zh-roberta-sentence-transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 411 Bytes
2940441 | 1 | {"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": 0.866895603436883, "lang_2_test_result_spearman": 0.8373392969215759, "lang_cross_test_result_spearman": 0.836742411771646, "lang_all_test_result_spearman": 0.8417338601593756, "languages": ["en", "zh"]} |