Instructions to use damlab/HIV_V3_Coreceptor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use damlab/HIV_V3_Coreceptor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="damlab/HIV_V3_Coreceptor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("damlab/HIV_V3_Coreceptor") model = AutoModelForSequenceClassification.from_pretrained("damlab/HIV_V3_Coreceptor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f5dfd12dd6ac8c5f31552028017a3394242754576773cc0e299d7b3ded0a64f
- Size of remote file:
- 1.68 GB
- SHA256:
- 6ed30a74d2e45f03a8cb6bb3498bfb6332735663502c4017f9741697456ca1e8
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