Instructions to use pborchert/bert-ic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pborchert/bert-ic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pborchert/bert-ic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pborchert/bert-ic") model = AutoModelForMaskedLM.from_pretrained("pborchert/bert-ic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: cc-by-4.0 | |
| language: | |
| - en | |
| pipeline_tag: fill-mask | |
| tags: | |
| - bert | |
| - industry classification | |
| library_name: transformers | |
| widget: | |
| - text: "Sanofi is in the [MASK] industry." | |
| - text: "The current ratio measures [MASK]." | |