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 pytorch_model.bin from Suchinthana/Finetuned-BERT-HotelClassification: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Suchinthana/Finetuned-BERT-HotelClassification/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Suchinthana/Finetuned-BERT-HotelClassification@refs/pr/1/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/Suchinthana/Finetuned-BERT-HotelClassification/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 5765e968781ea1d4cc9e1d5356b8e2cdd9d7f4943ded3f24561f6f186609fe17
- Size of remote file:
- 438 MB
- SHA256:
- 549557c55ff5da4a6206d403d1fc8f64f2468ab71978c57ae7377d25359442a9
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