Summarization
Transformers
Safetensors
Vietnamese
deberta-v2
feature-extraction
vietnamese
evaluation
reward-model
rlhf
cross-encoder
Instructions to use phuongntc/Multi_EvalSumViet2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phuongntc/Multi_EvalSumViet2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="phuongntc/Multi_EvalSumViet2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("phuongntc/Multi_EvalSumViet2") model = AutoModel.from_pretrained("phuongntc/Multi_EvalSumViet2") - Notebooks
- Google Colab
- Kaggle