Instructions to use Kk2k/Distilbert_domain_adapted_ecomm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kk2k/Distilbert_domain_adapted_ecomm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kk2k/Distilbert_domain_adapted_ecomm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kk2k/Distilbert_domain_adapted_ecomm") model = AutoModelForMaskedLM.from_pretrained("Kk2k/Distilbert_domain_adapted_ecomm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 626c3f1300b9942be0b2f2ac3604174b1f6aa03fa815e7fc5cc2ec609e86b2ae
- Size of remote file:
- 2.03 kB
- SHA256:
- f059a046cd20cf6f05eda8df4d1a6fa8679b36da0da859f48920124efb5f4838
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