Fill-Mask
Transformers
Safetensors
English
bert
protein
protbert
masked-language-modeling
bioinformatics
sequence-prediction
Instructions to use faceless-void/protbert-sequence-unmasking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faceless-void/protbert-sequence-unmasking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faceless-void/protbert-sequence-unmasking")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faceless-void/protbert-sequence-unmasking") model = AutoModelForMaskedLM.from_pretrained("faceless-void/protbert-sequence-unmasking") - Notebooks
- Google Colab
- Kaggle
Upload scheduler.pt with huggingface_hub
Browse files- scheduler.pt +3 -0
scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:8a37b914570a137609bc9fec92c7bb98c4b9c8f591f4b2562a18d5fdc7eb0ee2
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size 1064
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