Text Classification
Transformers
Safetensors
Vietnamese
roberta
cross-encoder
rerank
text-embeddings-inference
Instructions to use itdainb/PhoRanker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itdainb/PhoRanker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="itdainb/PhoRanker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("itdainb/PhoRanker") model = AutoModelForSequenceClassification.from_pretrained("itdainb/PhoRanker", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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@@ -124,7 +124,7 @@ In the following table, we provide various pre-trained Cross-Encoders together w
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```Plaintext
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@misc{PhoRanker,
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title={PhoRanker: A Cross-encoder Model for Vietnamese Text Ranking},
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author={Dai Nguyen Ba},
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year={2024},
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publisher={Huggingface},
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journal={huggingface repository},
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```Plaintext
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@misc{PhoRanker,
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title={PhoRanker: A Cross-encoder Model for Vietnamese Text Ranking},
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author={Dai Nguyen Ba ({ORCID:0009-0008-8559-3154})},
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year={2024},
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publisher={Huggingface},
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journal={huggingface repository},
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