Instructions to use Ppxndpxdd/tr_acc_80 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ppxndpxdd/tr_acc_80 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ppxndpxdd/tr_acc_80")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ppxndpxdd/tr_acc_80") model = AutoModelForSequenceClassification.from_pretrained("Ppxndpxdd/tr_acc_80", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Ppxndpxdd/tr_acc_80: direct link, hf CLI and curl.
- Browser
- Download file 842 MB
-
https://huggingface.co/Ppxndpxdd/tr_acc_80/resolve/main/optimizer.pt
- Command line
-
hf download hf://Ppxndpxdd/tr_acc_80/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Ppxndpxdd/tr_acc_80/resolve/main/optimizer.pt
842 MB
- Xet hash:
- e0c381484edbb2dd121dc95234ed3287eb85e954e17938814a5ee1b6cddf4ce3
- Size of remote file:
- 842 MB
- SHA256:
- 035bb3eb0535bd42613169511224092bc3d29ec337b67f6470223646a28dd799
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