Instructions to use AI4Protein/deep_bpe_1600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4Protein/deep_bpe_1600 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AI4Protein/deep_bpe_1600")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AI4Protein/deep_bpe_1600") model = AutoModelForMaskedLM.from_pretrained("AI4Protein/deep_bpe_1600", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 146 Bytes
9f8cb04 | 1 2 3 4 5 6 | {
"clean_up_tokenization_spaces": true,
"model_max_length": 1000000000000000019884624838656,
"tokenizer_class": "PreTrainedTokenizerFast"
}
|