Instructions to use PaddleCI/tiny-random-uie-m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- paddlenlp
How to use PaddleCI/tiny-random-uie-m with paddlenlp:
from paddlenlp.transformers import AutoTokenizer, UIEM tokenizer = AutoTokenizer.from_pretrained("PaddleCI/tiny-random-uie-m", from_hf_hub=True) model = UIEM.from_pretrained("PaddleCI/tiny-random-uie-m", from_hf_hub=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "UIEM" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "dtype": "float32", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 8, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "max_position_embeddings": 514, | |
| "model_type": "ernie_m", | |
| "num_attention_heads": 2, | |
| "num_hidden_layers": 2, | |
| "pad_token_id": 1, | |
| "paddlenlp_version": null, | |
| "type_vocab_size": 16, | |
| "vocab_size": 250002 | |
| } | |