Instructions to use DerivedFunction01/distilbert-finance-sec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DerivedFunction01/distilbert-finance-sec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DerivedFunction01/distilbert-finance-sec")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DerivedFunction01/distilbert-finance-sec") model = AutoModelForMaskedLM.from_pretrained("DerivedFunction01/distilbert-finance-sec") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e272bd142d1a5bdb878da58e3f298071b0403d1e080b17127d52a33e2a363461
- Size of remote file:
- 5.2 kB
- SHA256:
- ca7b20d7b179e77fcf056c7baddb4ec9265eaf82745f4180e1eaa4fa5a823651
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