Instructions to use Porameht/bert-base-th-cased-intent-booking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Porameht/bert-base-th-cased-intent-booking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Porameht/bert-base-th-cased-intent-booking")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Porameht/bert-base-th-cased-intent-booking") model = AutoModelForSequenceClassification.from_pretrained("Porameht/bert-base-th-cased-intent-booking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Porameht/bert-base-th-cased-intent-booking: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/Porameht/bert-base-th-cased-intent-booking/resolve/main/training_args.bin
- Command line
-
hf download hf://Porameht/bert-base-th-cased-intent-booking/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Porameht/bert-base-th-cased-intent-booking/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 365c9f072f492f51296c7e81404d1bf29306e234dcf650d3c44e8e931e52241d
- Size of remote file:
- 5.24 kB
- SHA256:
- ad4e9a78545ce6b81b8495f01b419f538a06a7ec9143abe160a7bc7b69d6fd72
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