Instructions to use Lucifer-nick/coconut_smiles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lucifer-nick/coconut_smiles with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Lucifer-nick/coconut_smiles")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Lucifer-nick/coconut_smiles") model = AutoModelForMaskedLM.from_pretrained("Lucifer-nick/coconut_smiles", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Lucifer-nick/coconut_smiles: direct link, hf CLI and curl.
- Browser
- Download file 328 Bytes
-
https://huggingface.co/Lucifer-nick/coconut_smiles/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Lucifer-nick/coconut_smiles/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/Lucifer-nick/coconut_smiles/resolve/main/tokenizer_config.json
328 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "max_len": 514, "special_tokens_map_file": "/content/drive/My Drive/Project De Novo/Molecule Transformer/SMILES_tokenized_PubChem_shard00_100k/checkpoint-60000/special_tokens_map.json", "full_tokenizer_file": null} | |