Instructions to use AdamCodd/distilbert-base-uncased-finetuned-sentiment-amazon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/distilbert-base-uncased-finetuned-sentiment-amazon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdamCodd/distilbert-base-uncased-finetuned-sentiment-amazon")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/distilbert-base-uncased-finetuned-sentiment-amazon") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/distilbert-base-uncased-finetuned-sentiment-amazon") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae9d59372b9bab6ef8639b2bc6e947e3ca549914913b461865c57f1c43f45edc
- Size of remote file:
- 268 MB
- SHA256:
- ea103ba85066c29903bae865d90c3ce0ff30448b1f5aea185f093a73049be5c8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.