Instructions to use mbouilloud/DataAug1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbouilloud/DataAug1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mbouilloud/DataAug1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mbouilloud/DataAug1") model = AutoModelForSequenceClassification.from_pretrained("mbouilloud/DataAug1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mbouilloud/DataAug1: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/mbouilloud/DataAug1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mbouilloud/DataAug1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mbouilloud/DataAug1/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- 9d589cf53a7445b6dba86bedc0302ab5621bb292991d53fc62eda7e449ba7198
- Size of remote file:
- 557 MB
- SHA256:
- 0f8a07f720ef7e4be7e2dded5bd449ce2ddcbcff00eb44362e733c4708870b9e
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