Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Jiebro02/learning_curve_overfit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jiebro02/learning_curve_overfit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jiebro02/learning_curve_overfit")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jiebro02/learning_curve_overfit") model = AutoModelForSequenceClassification.from_pretrained("Jiebro02/learning_curve_overfit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jiebro02/learning_curve_overfit: direct link, hf CLI and curl.
- Browser
- Download file 5.81 kB
-
https://huggingface.co/Jiebro02/learning_curve_overfit/resolve/main/training_args.bin
- Command line
-
hf download hf://Jiebro02/learning_curve_overfit/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jiebro02/learning_curve_overfit/resolve/main/training_args.bin
5.81 kB
- Xet hash:
- 7f65b123154c5b14a9d5a6e44a6b2258e71d23f42bc14e5353e0cb76f84b04fc
- Size of remote file:
- 5.81 kB
- SHA256:
- 6d18c6dd6e1481b49f6bfb49bdc164971e071b771001d32d18ad851eedd3723e
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