Instructions to use PoetschLab/GROVER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PoetschLab/GROVER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PoetschLab/GROVER")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PoetschLab/GROVER") model = AutoModelForMaskedLM.from_pretrained("PoetschLab/GROVER") - Inference
- Notebooks
- Google Colab
- Kaggle
| { | |
| "clean_up_tokenization_spaces": true, | |
| "do_lower_case": false, | |
| "model_max_length": 512, | |
| "special_tokens": { | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]" | |
| }, | |
| "tokenize_chinese_chars": false, | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "trust_remote_code": true | |
| } | |