Summarization
Transformers
Safetensors
Vietnamese
t5
text2text-generation
vit5
vietnamese
text-generation-inference
Instructions to use tmanh217/hlk-vit5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmanh217/hlk-vit5 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="tmanh217/hlk-vit5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tmanh217/hlk-vit5") model = AutoModelForSeq2SeqLM.from_pretrained("tmanh217/hlk-vit5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
HLK-ViT5
HLK-ViT5 là mô hình tóm tắt văn bản tiếng Việt được fine-tune từ VietAI/vit5-base.
Base model
VietAI/vit5-base
Task
- Vietnamese text summarization
- Text-to-text generation
Framework
- PyTorch
- Hugging Face Transformers
Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model_id = "tmanh217/hlk-vit5"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
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Model tree for tmanh217/hlk-vit5
Base model
VietAI/vit5-base