Instructions to use Gflorent/BERT_baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gflorent/BERT_baseline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gflorent/BERT_baseline")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gflorent/BERT_baseline") model = AutoModelForSequenceClassification.from_pretrained("Gflorent/BERT_baseline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6867403683cf35af82e30a94546c115a4a722c332f750eb303c4d557ee10ce2f
- Size of remote file:
- 4.73 kB
- SHA256:
- 8ad3e066977938c8b4d10198e95d7ca3b73230fd24d433572a542f974096b032
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