Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use egerber1/classifier-de1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egerber1/classifier-de1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="egerber1/classifier-de1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("egerber1/classifier-de1") model = AutoModelForSequenceClassification.from_pretrained("egerber1/classifier-de1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from egerber1/classifier-de1: direct link, hf CLI and curl.
- Browser
- Download file 5.65 kB
-
https://huggingface.co/egerber1/classifier-de1/resolve/main/training_args.bin
- Command line
-
hf download hf://egerber1/classifier-de1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/egerber1/classifier-de1/resolve/main/training_args.bin
5.65 kB
- Xet hash:
- cafa2ac12a223ad5c0ad754865afa2331d0e5053c627ed1d4396832982bcbd23
- Size of remote file:
- 5.65 kB
- SHA256:
- 63980f5d984bf7904756283bb3be9e681256f4e8721a850f104784b13ad804c1
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