Instructions to use hf-internal-testing/tiny-random-prophetnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-prophetnet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-prophetnet")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-prophetnet") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-prophetnet") - Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "x_sep_token": "[X_SEP]", "pad_token": "[PAD]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": "/home/lysandre/.cache/huggingface/transformers/73e9134d07adccf5cf38d24c2f241f87e3febd91b209b279fff2741c9ff2ab4f.6fa7d8b91dc65e73f96549c829087df43aa7359e1d576908a012e7747d67c6c2", "tokenizer_file": null, "name_or_path": "microsoft/prophetnet-large-uncased", "tokenizer_class": "ProphetNetTokenizer"} |