Text Classification
Transformers
Safetensors
English
bert
biomedicine
classification
amyloids
antibodies
pubmed
text-embeddings-inference
Instructions to use kotsonor/BiomedBERT-Amyloid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kotsonor/BiomedBERT-Amyloid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kotsonor/BiomedBERT-Amyloid")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kotsonor/BiomedBERT-Amyloid") model = AutoModelForSequenceClassification.from_pretrained("kotsonor/BiomedBERT-Amyloid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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library_name: transformers
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# BiomedBERT-Amyloid
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- **Institution:** Bioinformatics and Multiomics Analysis Laboratory, Clinical Research Centre, Medical University of Bialystok.
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- **Funding Source:** National Science Center, Poland, via the SONATA 19 grant.
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- **Project No:** DEC-2023/51/D/NZ7/02847.
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- **Project Title:** “Taming aggregation with AmyloGraphem 2.0: database and predictive model of amyloid self-organization of modulators”.
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library_name: transformers
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tags:
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- biomedicine
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- classification
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- amyloids
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- antibodies
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- pubmed
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license: apache-2.0
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language:
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- en
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base_model:
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- microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
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# BiomedBERT-Amyloid
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- **Institution:** Bioinformatics and Multiomics Analysis Laboratory, Clinical Research Centre, Medical University of Bialystok.
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- **Funding Source:** National Science Center, Poland, via the SONATA 19 grant.
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- **Project No:** DEC-2023/51/D/NZ7/02847.
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- **Project Title:** “Taming aggregation with AmyloGraphem 2.0: database and predictive model of amyloid self-organization of modulators”.
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