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 pytorch_model.bin from aari1995/German_Sentiment: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/aari1995/German_Sentiment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://aari1995/German_Sentiment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aari1995/German_Sentiment/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 007bd717a55f0a7d858518d7cf06749ed1a2223377ede966cf6fc3531ca09a84
- Size of remote file:
- 1.34 GB
- SHA256:
- cd6455298f7f91f4d1a1c764842dc03d8258e83b35c0e91384f769875359b875
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