Instructions to use prajjwal1/bert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prajjwal1/bert-tiny with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prajjwal1/bert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from prajjwal1/bert-tiny: direct link, hf CLI and curl.
- Browser
- Download file 285 Bytes
-
https://huggingface.co/prajjwal1/bert-tiny/resolve/7d1bceeafe4bf36e9f7d75104bb5fa5b03a040f9/config.json
- Command line
-
hf download hf://prajjwal1/bert-tiny@7d1bceeafe4bf36e9f7d75104bb5fa5b03a040f9/config.json
-
curl -L -o config.json https://huggingface.co/prajjwal1/bert-tiny/resolve/7d1bceeafe4bf36e9f7d75104bb5fa5b03a040f9/config.json
285 Bytes
| {"hidden_size": 128, "hidden_act": "gelu", "initializer_range": 0.02, "vocab_size": 30522, "hidden_dropout_prob": 0.1, "num_attention_heads": 2, "type_vocab_size": 2, "max_position_embeddings": 512, "num_hidden_layers": 2, "intermediate_size": 512, "attention_probs_dropout_prob": 0.1} |