Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use BiggieW/classification_tnews_more_imbalanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiggieW/classification_tnews_more_imbalanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BiggieW/classification_tnews_more_imbalanced")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BiggieW/classification_tnews_more_imbalanced") model = AutoModelForSequenceClassification.from_pretrained("BiggieW/classification_tnews_more_imbalanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BiggieW/classification_tnews_more_imbalanced: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/BiggieW/classification_tnews_more_imbalanced/resolve/main/training_args.bin
- Command line
-
hf download hf://BiggieW/classification_tnews_more_imbalanced/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BiggieW/classification_tnews_more_imbalanced/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- c13e6e42d23664731e855c72b1f50725bbbbb00987bc7f4adfc71386a19e6687
- Size of remote file:
- 3.45 kB
- SHA256:
- c0bba0d9257ddf7c4cf57d75541ebe479af665e6f887a628fa0664c690704896
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