Instructions to use Jehadoumer/task2B-preprocessed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jehadoumer/task2B-preprocessed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jehadoumer/task2B-preprocessed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jehadoumer/task2B-preprocessed") model = AutoModelForSequenceClassification.from_pretrained("Jehadoumer/task2B-preprocessed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jehadoumer/task2B-preprocessed: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/Jehadoumer/task2B-preprocessed/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jehadoumer/task2B-preprocessed/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jehadoumer/task2B-preprocessed/resolve/main/pytorch_model.bin
541 MB
- Xet hash:
- 7c4952e4ec5fd1eadb9fd510b0b1cc37996cbea2f80190a888d679108c954e4d
- Size of remote file:
- 541 MB
- SHA256:
- 6a683ce70ae4bde43d2a191a8556ec2d0e1d4afa6770a6280393b84917c7fa84
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