Instructions to use Suchinthana/Finetuned-BERT-HotelClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Suchinthana/Finetuned-BERT-HotelClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Suchinthana/Finetuned-BERT-HotelClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Suchinthana/Finetuned-BERT-HotelClassification") model = AutoModelForSequenceClassification.from_pretrained("Suchinthana/Finetuned-BERT-HotelClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Suchinthana/Finetuned-BERT-HotelClassification: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/Suchinthana/Finetuned-BERT-HotelClassification/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Suchinthana/Finetuned-BERT-HotelClassification@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Suchinthana/Finetuned-BERT-HotelClassification/resolve/refs%2Fpr%2F1/training_args.bin
3.9 kB
- Xet hash:
- 2400c73a2e3ec7ab76c070fd074dc04fee052275dc7e6fd43101c1a1dc9ff0e1
- Size of remote file:
- 3.9 kB
- SHA256:
- 351d6ac3eace9b993bd261a4529d83ee5d925587b1c68ea70a266ef02b03959d
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