Instructions to use UmerKhan261/Fine-Tuned_BERT_German_Text_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UmerKhan261/Fine-Tuned_BERT_German_Text_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UmerKhan261/Fine-Tuned_BERT_German_Text_Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UmerKhan261/Fine-Tuned_BERT_German_Text_Classification") model = AutoModelForSequenceClassification.from_pretrained("UmerKhan261/Fine-Tuned_BERT_German_Text_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from UmerKhan261/Fine-Tuned_BERT_German_Text_Classification: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/UmerKhan261/Fine-Tuned_BERT_German_Text_Classification/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://UmerKhan261/Fine-Tuned_BERT_German_Text_Classification@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/UmerKhan261/Fine-Tuned_BERT_German_Text_Classification/resolve/refs%2Fpr%2F1/pytorch_model.bin
436 MB
- Xet hash:
- a7cadd573f362e3dcc944f80634bfc0afe7261fe69726e99d6cc2c1274ae42ca
- Size of remote file:
- 436 MB
- SHA256:
- 5605a3de13c0b97482d3957f99a6288dbf15a236f68e8154e6a66d61e11d7561
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