Instructions to use Noodle-bg/BERT_Text_classification_clean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Noodle-bg/BERT_Text_classification_clean with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Noodle-bg/BERT_Text_classification_clean")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Noodle-bg/BERT_Text_classification_clean") model = AutoModelForSequenceClassification.from_pretrained("Noodle-bg/BERT_Text_classification_clean", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Noodle-bg/BERT_Text_classification_clean: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/Noodle-bg/BERT_Text_classification_clean/resolve/main/training_args.bin
- Command line
-
hf download hf://Noodle-bg/BERT_Text_classification_clean/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Noodle-bg/BERT_Text_classification_clean/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 1f44af7abe681dbb38651be0b8cca8ab2b0c358643313d5df3a70d7eb981ed91
- Size of remote file:
- 4.66 kB
- SHA256:
- 9c7a01f69c756827671e531976602bb92dafd552bef459e8ad444d5975870329
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