Instructions to use monsoon-nlp/bert-base-thai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monsoon-nlp/bert-base-thai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="monsoon-nlp/bert-base-thai")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("monsoon-nlp/bert-base-thai") model = AutoModel.from_pretrained("monsoon-nlp/bert-base-thai", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from monsoon-nlp/bert-base-thai: direct link, hf CLI and curl.
- Browser
- Download file 405 Bytes
-
https://huggingface.co/monsoon-nlp/bert-base-thai/resolve/refs%2Fpr%2F1/config.json
- Command line
-
hf download hf://monsoon-nlp/bert-base-thai@refs/pr/1/config.json
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curl -L -o config.json https://huggingface.co/monsoon-nlp/bert-base-thai/resolve/refs%2Fpr%2F1/config.json
405 Bytes
| { | |
| "architectures": [ | |
| "BertModel" | |
| ], | |
| "embedding_size": 768, | |
| "model_type": "bert", | |
| "attention_probs_dropout_prob": 0.1, | |
| "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, | |
| "type_vocab_size": 2, | |
| "vocab_size": 25004 | |
| } | |