Text Classification
Transformers
PyTorch
genomics
virology
dna
virus
transmissibility
r0
hvue-v2
custom_code
Instructions to use duttaprat/HViLM-R0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use duttaprat/HViLM-R0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="duttaprat/HViLM-R0", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("duttaprat/HViLM-R0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 736eebe42d54a4f0f49e8822abf645f635f921437d8b3976c6fb05818bf81d1c
- Size of remote file:
- 468 MB
- SHA256:
- 60be8bb22f64391d069fd1682930ad498809b31b14dc4aedc0b55b7b8bc7c142
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