Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use jnwulff/classifier-chapter4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jnwulff/classifier-chapter4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jnwulff/classifier-chapter4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jnwulff/classifier-chapter4") model = AutoModelForSequenceClassification.from_pretrained("jnwulff/classifier-chapter4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jnwulff/classifier-chapter4: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/jnwulff/classifier-chapter4/resolve/main/training_args.bin
- Command line
-
hf download hf://jnwulff/classifier-chapter4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jnwulff/classifier-chapter4/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 7b3cd418b03788fa92a830ab89be40c2e6972e770b007b288a898fcf055fa5fe
- Size of remote file:
- 5.3 kB
- SHA256:
- ad1ddcc451f0c833f5b3c62f6dfd6cdb37e5d5fad01c509d4139ea5746f16dbb
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