Instructions to use optimum-intel-internal-testing/tiny-random-squeezebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum-intel-internal-testing/tiny-random-squeezebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="optimum-intel-internal-testing/tiny-random-squeezebert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("optimum-intel-internal-testing/tiny-random-squeezebert") model = AutoModel.from_pretrained("optimum-intel-internal-testing/tiny-random-squeezebert") - Notebooks
- Google Colab
- Kaggle
File size: 342 Bytes
76ca583 | 1 | {"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, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "squeezebert/squeezebert-uncased", "tokenizer_class": "SqueezeBertTokenizer"} |