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:
- 9a804fe2cdbf874ef9acaad0285376e06d302588d41998ff05973b4ebf92e328
- Size of remote file:
- 4.28 kB
- SHA256:
- 3f798d3616fbc0d2ba69b9cc82de9ece969255ffd12cb626c1c7dfe715ec417a
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