Instructions to use VCNC/bert_piezas2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/bert_piezas2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/bert_piezas2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/bert_piezas2") model = AutoModelForSequenceClassification.from_pretrained("VCNC/bert_piezas2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f995ea42a87a814b49e6a728076b5dfd60677a1e1d3fdd05fc89697047558dff
- Size of remote file:
- 692 MB
- SHA256:
- aa2eed5f147d78e1c2c730e07515d576e6080bed16eac8eb1a25dafc91541a22
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