Instructions to use oliverguhr/german-sentiment-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oliverguhr/german-sentiment-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="oliverguhr/german-sentiment-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("oliverguhr/german-sentiment-bert") model = AutoModelForSequenceClassification.from_pretrained("oliverguhr/german-sentiment-bert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from oliverguhr/german-sentiment-bert: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/oliverguhr/german-sentiment-bert/resolve/main/model.safetensors
- Command line
-
hf download hf://oliverguhr/german-sentiment-bert/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/oliverguhr/german-sentiment-bert/resolve/main/model.safetensors
436 MB
- Xet hash:
- 8ead811461a16b84fe6e778f8604f508a2bac967469edbd76612a32f1a691fe3
- Size of remote file:
- 436 MB
- SHA256:
- 95e55a158e374856e7066de7d23aecf670fd6e5bef799baa2e205b13e153fcba
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