Transformers
PyTorch
TensorFlow
Arabic
t5
Arabic T5
MSA
Twitter
Arabic Dialect
Arabic Machine Translation
Arabic Text Summarization
Arabic News Title and Question Generation
Arabic Paraphrasing and Transliteration
Arabic Code-Switched Translation
text-generation-inference
Instructions to use UBC-NLP/AraT5-msa-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/AraT5-msa-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UBC-NLP/AraT5-msa-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
elmadany commited on
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Parent(s): 7847e48
commit from elmadany
Browse files- config.json +0 -3
config.json
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{
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"_name_or_path": "/project/6007993/elmadany/T5/ArT5_models/MSA_1M_small",
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"architectures": [
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"T5ForConditionalGeneration"
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],
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"d_ff": 1024,
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"d_kv": 64,
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"d_model": 512,
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{
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"_name_or_path": "/project/6007993/elmadany/T5/ArT5_models/MSA_1M_small",
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"d_ff": 1024,
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"d_kv": 64,
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"d_model": 512,
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