Sentence Similarity
Transformers
PyTorch
German
English
xlm-roberta
feature-extraction
semantic textual similarity
sts
semantic search
sentence similarity
paraphrasing
sentence-transformer
text-embeddings-inference
Instructions to use PM-AI/sts_paraphrase_xlm-roberta-base_de-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PM-AI/sts_paraphrase_xlm-roberta-base_de-en with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("PM-AI/sts_paraphrase_xlm-roberta-base_de-en") model = AutoModel.from_pretrained("PM-AI/sts_paraphrase_xlm-roberta-base_de-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from PM-AI/sts_paraphrase_xlm-roberta-base_de-en: direct link, hf CLI and curl.
- Browser
- Download file 730 Bytes
-
https://huggingface.co/PM-AI/sts_paraphrase_xlm-roberta-base_de-en/resolve/main/config.json
- Command line
-
hf download hf://PM-AI/sts_paraphrase_xlm-roberta-base_de-en/config.json
-
curl -L -o config.json https://huggingface.co/PM-AI/sts_paraphrase_xlm-roberta-base_de-en/resolve/main/config.json
730 Bytes
| { | |
| "_name_or_path": "models/sts_paraphrase_xlm-roberta-base_de-en/", | |
| "architectures": [ | |
| "XLMRobertaModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.16.2", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 250002 | |
| } | |