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")# pip install -U transformers accelerate # 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 flax_model.msgpack 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/flax_model.msgpack
- Command line
-
hf download hf://oliverguhr/german-sentiment-bert/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/oliverguhr/german-sentiment-bert/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- c00a686d1c6076f684d7716a323863675c95294ce82dc95b8d71fd93270940c0
- Size of remote file:
- 436 MB
- SHA256:
- 61ad9558ae827e91a90ba2cd4326132e4fd62e47fae76bb6e0be19c7f1ffe435
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