Instructions to use hang1n/t5-large_Prefix_Tuning_seq2seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hang1n/t5-large_Prefix_Tuning_seq2seq with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hang1n/t5-large_Prefix_Tuning_seq2seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 370 Bytes
db29734 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"auto_mapping": null,
"base_model_name_or_path": "t5-large",
"encoder_hidden_size": 1024,
"inference_mode": true,
"num_attention_heads": 16,
"num_layers": 24,
"num_transformer_submodules": 2,
"num_virtual_tokens": 20,
"peft_type": "PREFIX_TUNING",
"prefix_projection": false,
"revision": null,
"task_type": "SEQ_2_SEQ_LM",
"token_dim": 1024
} |