Instructions to use YagiASAFAS/MSPoliBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YagiASAFAS/MSPoliBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YagiASAFAS/MSPoliBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YagiASAFAS/MSPoliBERT") model = AutoModelForSequenceClassification.from_pretrained("YagiASAFAS/MSPoliBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1320c7bf12fe5a2e994784ee09a52acfc1430e4889a858c82c607b4202a81af
- Size of remote file:
- 438 MB
- SHA256:
- 29c132e3e01113fc5c0129db73b1f71c36421536e9a0e78ed91d6f86f1b0684c
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