Instructions to use AI4Protein/deep_unigram_50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4Protein/deep_unigram_50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AI4Protein/deep_unigram_50")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AI4Protein/deep_unigram_50") model = AutoModelForMaskedLM.from_pretrained("AI4Protein/deep_unigram_50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add model card and metadata
Verified signatureThis PR adds a model card with the appropriate metadata, including the `pipeline_tag`, `library_name`, and `license`. It also includes a brief description of the model and links to the paper and GitHub repository.5ad9933
-
Upload RoFormerForMaskedLM
cdab241 -
Upload tokenizer
84ed39b -
Upload config
72eaaca -
initial commit
fa2b1f9