Instructions to use bjbjbj/classifier-chapter4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bjbjbj/classifier-chapter4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bjbjbj/classifier-chapter4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bjbjbj/classifier-chapter4") model = AutoModelForSequenceClassification.from_pretrained("bjbjbj/classifier-chapter4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bjbjbj/classifier-chapter4: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/bjbjbj/classifier-chapter4/resolve/main/training_args.bin
- Command line
-
hf download hf://bjbjbj/classifier-chapter4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bjbjbj/classifier-chapter4/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- ab94c4a427b7ab26dcd9b7640fb7e630b349feeed439668258318488c0aaacaa
- Size of remote file:
- 5.24 kB
- SHA256:
- c9921f1079952a1d87d142b0cca9514d05e25f99001c65ba1c243ea851eee9e1
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