Instructions to use leonweber/semantic_relations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leonweber/semantic_relations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leonweber/semantic_relations")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leonweber/semantic_relations") model = AutoModelForSequenceClassification.from_pretrained("leonweber/semantic_relations", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "/Users/leonweber/Downloads/18-17-29/", "do_basic_tokenize": true, "never_split": null, "id2label": {"0": "TREAT_FOR_DIS", "1": "PREVENT", "2": "SIDE_EFF"}, "tokenizer_class": "BertTokenizer"} |