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
File size: 284 Bytes
1d1d018 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"clean_up_tokenization_spaces": true,
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"model_max_length": 250,
"pad_token": "[PAD]",
"padding_side": "right",
"sep_token": "[SEP]",
"token": null,
"tokenizer_class": "PreTrainedTokenizerFast",
"unk_token": "[UNK]"
}
|