Text Classification
Transformers
PyTorch
Safetensors
German
bert
deepset/gbert-large
text-embeddings-inference
Instructions to use aari1995/German_Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aari1995/German_Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aari1995/German_Sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aari1995/German_Sentiment") model = AutoModelForSequenceClassification.from_pretrained("aari1995/German_Sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aari1995/German_Sentiment: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/aari1995/German_Sentiment/resolve/main/training_args.bin
- Command line
-
hf download hf://aari1995/German_Sentiment/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aari1995/German_Sentiment/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- 5c1025e6af10280ffdafabd76498ce812758e662d5127a9a4031376f56d28ebe
- Size of remote file:
- 3.9 kB
- SHA256:
- a42fbad6293be2064cb40ea4e02e734ac40ed08547b56dda5b8d2d194e81f1d4
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