Feature Extraction
Transformers
Safetensors
English
cronformer
cron
schedules
text-to-cron
structured-prediction
custom-code
custom_code
Eval Results (legacy)
Instructions to use impalasys/cronformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use impalasys/cronformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="impalasys/cronformer", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("impalasys/cronformer", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 128, | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizerFast", | |
| "unk_token": "[UNK]" | |
| } | |