Instructions to use hellonlp/simcse-roberta-base-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hellonlp/simcse-roberta-base-zh with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hellonlp/simcse-roberta-base-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from hellonlp/simcse-roberta-base-zh: direct link, hf CLI and curl.
- Browser
- Download file 520 Bytes
-
https://huggingface.co/hellonlp/simcse-roberta-base-zh/resolve/main/config.json
- Command line
-
hf download hf://hellonlp/simcse-roberta-base-zh/config.json
-
curl -L -o config.json https://huggingface.co/hellonlp/simcse-roberta-base-zh/resolve/main/config.json
520 Bytes
| { | |
| "attention_probs_dropout_prob": 0.1, | |
| "directionality": "bidi", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "max_position_embeddings": 512, | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "type_vocab_size": 2, | |
| "vocab_size": 21128 | |
| } | |