Instructions to use ryanyip7777/intent_bert_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ryanyip7777/intent_bert_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ryanyip7777/intent_bert_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ryanyip7777/intent_bert_classifier") model = AutoModelForSequenceClassification.from_pretrained("ryanyip7777/intent_bert_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ryanyip7777/intent_bert_classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.07 kB
-
https://huggingface.co/ryanyip7777/intent_bert_classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://ryanyip7777/intent_bert_classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ryanyip7777/intent_bert_classifier/resolve/main/training_args.bin
1.07 kB
- Xet hash:
- 14c477282b3e6c92e0acf7ef0d95a4361863392993fc07e90d2bffea453213e1
- Size of remote file:
- 1.07 kB
- SHA256:
- 1d83cfbe9e3ce7ee5b2769cda212ca8e1ebe8d0c2a2cefc9862c4b93d9c16089
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.