Instructions to use admko/sembr2023-distilbert-base-uncased-finetuned-sst-2-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use admko/sembr2023-distilbert-base-uncased-finetuned-sst-2-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="admko/sembr2023-distilbert-base-uncased-finetuned-sst-2-english")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("admko/sembr2023-distilbert-base-uncased-finetuned-sst-2-english") model = AutoModelForTokenClassification.from_pretrained("admko/sembr2023-distilbert-base-uncased-finetuned-sst-2-english") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ff724d0188978ab8d5f498b8070aa8548172a47d958d91ea31f05d85f5c91af
- Size of remote file:
- 266 MB
- SHA256:
- 0fa69df9681c32b99b8eead25b723e91c554ae53639328d32ede86f0fb6844cf
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