Text Classification
Transformers
PyTorch
Vietnamese
vietnamese
summarization
evaluation
cross-encoder
research
Instructions to use phuongntc/MultiEvalVietSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phuongntc/MultiEvalVietSum with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="phuongntc/MultiEvalVietSum")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("phuongntc/MultiEvalVietSum", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 545 Bytes
2bcedff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"backend": "tokenizers",
"bos_token": "<bos>",
"clean_up_tokenization_spaces": false,
"cls_token": "<bos>",
"eos_token": "<eos>",
"extra_special_tokens": [
"<start_of_turn>",
"<end_of_turn>"
],
"is_local": false,
"mask_token": "<mask>",
"model_input_names": [
"input_ids",
"attention_mask"
],
"model_max_length": 8192,
"pad_token": "<pad>",
"padding_side": "right",
"sep_token": "<eos>",
"spaces_between_special_tokens": false,
"tokenizer_class": "TokenizersBackend",
"unk_token": "<unk>"
}
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