Instructions to use ronig/protein_biencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ronig/protein_biencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ronig/protein_biencoder", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ronig/protein_biencoder", trust_remote_code=True) model = AutoModel.from_pretrained("ronig/protein_biencoder", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 170 Bytes
d40c4dd | 1 2 3 4 5 6 7 | {
"clean_up_tokenization_spaces": true,
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad>",
"tokenizer_class": "PreTrainedTokenizerFast"
}
|