Instructions to use Chessmen/fine_tuned_distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chessmen/fine_tuned_distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Chessmen/fine_tuned_distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Chessmen/fine_tuned_distilbert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("Chessmen/fine_tuned_distilbert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d8febcb18e0e95c3aee484c2758c63897b9d224f940dc20a09402eff2f71335
- Size of remote file:
- 5.24 kB
- SHA256:
- d300f8cac52844a5f0c8280c2941366a386056d55a3cc40165c5874f1b7cd5b2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.