Instructions to use Kk2k/distilbert_base_uncased_finetuned_custom_ecomm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kk2k/distilbert_base_uncased_finetuned_custom_ecomm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kk2k/distilbert_base_uncased_finetuned_custom_ecomm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kk2k/distilbert_base_uncased_finetuned_custom_ecomm") model = AutoModelForSequenceClassification.from_pretrained("Kk2k/distilbert_base_uncased_finetuned_custom_ecomm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot