Instructions to use isikz/esm1b_ft_phosphosite_data_combined with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isikz/esm1b_ft_phosphosite_data_combined with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="isikz/esm1b_ft_phosphosite_data_combined")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("isikz/esm1b_ft_phosphosite_data_combined") model = AutoModelForMaskedLM.from_pretrained("isikz/esm1b_ft_phosphosite_data_combined", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4ec8f6e3700caaa3d63384dcff15440371c18ef47ac181d3d58a71eb81e6cf6
- Size of remote file:
- 2.61 GB
- SHA256:
- fcd0662a81a99425d6f563eb63c8ab2db97eb80361fee31f21a42888d7d05cf9
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