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-tweet-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/AraT5-tweet-small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UBC-NLP/AraT5-tweet-small", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 540 Bytes
80b2cee 9e11c1a 80b2cee | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"d_ff": 1024,
"d_kv": 64,
"d_model": 512,
"decoder_start_token_id": 0,
"dropout_rate": 0.1,
"eos_token_id": 1,
"feed_forward_proj": "gated-gelu",
"gradient_checkpointing": false,
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"layer_norm_epsilon": 1e-06,
"model_type": "t5",
"num_decoder_layers": 12,
"num_heads": 6,
"num_layers": 8,
"output_past": true,
"pad_token_id": 0,
"relative_attention_num_buckets": 32,
"transformers_version": "4.9.2",
"use_cache": true,
"vocab_size": 110080
}
|