Question Answering
Transformers
PyTorch
TensorFlow
JAX
Vietnamese
t5
text2text-generation
summarization
translation
text-generation-inference
Instructions to use VietAI/vit5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VietAI/vit5-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VietAI/vit5-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("VietAI/vit5-large") model = AutoModelForSeq2SeqLM.from_pretrained("VietAI/vit5-large") - Notebooks
- Google Colab
- Kaggle
Commit ·
e17ecdf
1
Parent(s): b4c595d
Update config.json
Browse filesupdate length for testing
- config.json +1 -0
config.json
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@@ -12,6 +12,7 @@
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"layer_norm_epsilon": 1e-06,
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"model_type": "t5",
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"num_decoder_layers": 24,
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"num_heads": 16,
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"layer_norm_epsilon": 1e-06,
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"max_length": 512,
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"model_type": "t5",
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"num_decoder_layers": 24,
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"num_heads": 16,
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