Text Classification
Transformers
Safetensors
bert
Trained with AutoTrain
protein-classification
protbert
antiobiotic-resistance
text-embeddings-inference
Instructions to use as-cle-bert/resistBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use as-cle-bert/resistBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="as-cle-bert/resistBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("as-cle-bert/resistBERT") model = AutoModelForSequenceClassification.from_pretrained("as-cle-bert/resistBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd89c461b456ef4b344225b7bab104d46feac58a8fb389a058063de07c20b60a
- Size of remote file:
- 3.36 GB
- SHA256:
- 9309b9d765925a9e41447d54c63767cfe3285429cae7a8e089794f2e91b70bb1
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