Instructions to use AscoraDev/sitolub.molgen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AscoraDev/sitolub.molgen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AscoraDev/sitolub.molgen")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AscoraDev/sitolub.molgen") model = AutoModelForSeq2SeqLM.from_pretrained("AscoraDev/sitolub.molgen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 534 Bytes
7fad9cf | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"model_max_length": 512,
"name_or_path": "/Users/indrapriyadarsinis/Desktop/Indra/MVP_v1/downstream/rhizome/src/rhizome/modelstore/zinc22-16B-tokenizer",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"special_tokens_map_file": "/u/indra/.cache/huggingface/transformers/410b9713b9ff338491c4439bb9c3426a17c79e66c5a02f0a729b5455a334037a.7da70648c6cb9951e284c9685f9ba7ae083dd59ed1d6d84bdfc0584a4ea94b6d",
"tokenizer_class": "PreTrainedTokenizerFast",
"unk_token": "[UNK]"
}
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