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
File size: 314 Bytes
134f3a1 587ca32 5e45af8 587ca32 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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
}
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