Instructions to use Jehadoumer/task2a-preprocessed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jehadoumer/task2a-preprocessed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jehadoumer/task2a-preprocessed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jehadoumer/task2a-preprocessed") model = AutoModelForSequenceClassification.from_pretrained("Jehadoumer/task2a-preprocessed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jehadoumer/task2a-preprocessed: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/Jehadoumer/task2a-preprocessed/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Jehadoumer/task2a-preprocessed@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jehadoumer/task2a-preprocessed/resolve/refs%2Fpr%2F1/training_args.bin
4.03 kB
- Xet hash:
- 6ea764e1b5d312a5c23ecfc9103eb90b8c10d2d86d944e58f05942671b32901d
- Size of remote file:
- 4.03 kB
- SHA256:
- a91b374f288da84b14309d9828e4a52cad0d1ab8ecd5101a5bec00ab7d715c7e
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