Instructions to use alexandrainst/da-subjectivivity-classification-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexandrainst/da-subjectivivity-classification-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alexandrainst/da-subjectivivity-classification-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alexandrainst/da-subjectivivity-classification-base") model = AutoModelForSequenceClassification.from_pretrained("alexandrainst/da-subjectivivity-classification-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08bdfd8b805e2f5d590bb4f2de18f24e148b86fb148cbe988de6abb1f6e9e8ff
- Size of remote file:
- 443 MB
- SHA256:
- 1d10822267e3de12b0433d316feca47edc195cfcca1421630df0092328c470f7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.