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 tf_model.h5 from UmerKhan261/Fine-Tuned_BERT_German_Text_Classification: direct link, hf CLI and curl.
- Browser
- Download file 437 MB
-
https://huggingface.co/UmerKhan261/Fine-Tuned_BERT_German_Text_Classification/resolve/main/tf_model.h5
- Command line
-
hf download hf://UmerKhan261/Fine-Tuned_BERT_German_Text_Classification/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/UmerKhan261/Fine-Tuned_BERT_German_Text_Classification/resolve/main/tf_model.h5
437 MB
- Xet hash:
- a51a63c674a635e8bedd1a1279e1937dde079b5bd846e944f861d69220b94b5a
- Size of remote file:
- 437 MB
- SHA256:
- bed180afac4af42bc146714c43472d5725b5269cde06bdd09eb895c7864a1822
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