Instructions to use Codemaster67/Olmo_spe_tokenizer_300SPE_TOKENS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Codemaster67/Olmo_spe_tokenizer_300SPE_TOKENS with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Codemaster67/Olmo_spe_tokenizer_300SPE_TOKENS", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add SPE tokenizer (434 SMILES subword tokens) + <|start_of_smiles|>/<|end_of_smiles|> special tokens. Trained on 2M ZINC20 + 2M ChEMBL canonical SMILES. SPE vocab_size=300, min_freq=4000.
9f054a4 verified | { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|start_of_smiles|>", | |
| "<|end_of_smiles|>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|padding|>", | |
| "tokenizer_class": "GPTNeoXTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": null | |
| } | |