Instructions to use dnagpt/dnagpt_unigram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dnagpt/dnagpt_unigram with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dnagpt/dnagpt_unigram")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dnagpt/dnagpt_unigram") model = AutoModel.from_pretrained("dnagpt/dnagpt_unigram", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from dnagpt/dnagpt_unigram: direct link, hf CLI and curl.
- Browser
- Download file 339 Bytes
-
https://huggingface.co/dnagpt/dnagpt_unigram/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://dnagpt/dnagpt_unigram/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/dnagpt/dnagpt_unigram/resolve/main/tokenizer_config.json
339 Bytes
| { | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<cls>", | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "padding_side": "left", | |
| "sep_token": "<sep>", | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "unk_token": "<unk>" | |
| } | |