Instructions to use ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2") model = AutoModelForSequenceClassification.from_pretrained("ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2/resolve/main/training_args.bin
- Command line
-
hf download hf://ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ThuyNT03/CS505-Classifier-T4_predictLabel_a1_v2/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 90dae71355c12842b753a289c3f62f77e44b73ed53488bf671ff5cef3367ca8b
- Size of remote file:
- 4.92 kB
- SHA256:
- e639059c3e7dcf1ee3ce70db589eb6e1c9a2fffa1e6a2754a4890568d3b8ac48
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.