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
- Xet hash:
- f3bfcd692cc171e30873394653925f8a5c889584a7fd7e6302f3d0b31eb7256d
- Size of remote file:
- 5.05 kB
- SHA256:
- 8462576be3281ab4b1beb4bd4b38156fb1539801f54ec651b2992af37c85eba8
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