Text Classification
Transformers
Safetensors
bert
proteins
Biology
classifier
text-embeddings-inference
Instructions to use oohtmeel/Bert_protein_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oohtmeel/Bert_protein_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="oohtmeel/Bert_protein_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("oohtmeel/Bert_protein_classifier") model = AutoModelForSequenceClassification.from_pretrained("oohtmeel/Bert_protein_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -20,4 +20,4 @@ outputs probability scores. (How likely is it that this sequence belongs to this
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The way you use this model for a demo is, you paste a protein sequence
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into the inference box and it outputs the relevant probabilities that certain GO terms are
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associated with that sequence.
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For example
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The way you use this model for a demo is, you paste a protein sequence
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into the inference box and it outputs the relevant probabilities that certain GO terms are
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associated with that sequence.
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For example MMSTTHLLVFLLGVVTLTTPTFGTYESPNYGKPPTPVFKPPKVKPPPYEPKPPVYEPPKKEKPEPKPPVYAPPKKEKHGPKPTMYEPPKKEKPEPKPPVYTPPKKEVPKPKPPVYEPPKKEKPEPKPPIYTPPKKEKPEPKPPVYEPPKKEKPEPKPPVYTPPKKEKPEPKPPVYEPPKKPPMYEPKPPKPPVYTPPKKEKPEPKPPMYEPPKKPPMYEPKPPKPPVYTPPKKEKPEPKPPMYQPPNNPPIYEPKPPKPPVYAPPKEEKPKPKPPVYEPPAHEPPYGHYPGHPPLGKPQ
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