Instructions to use havens2/scideberta_SER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use havens2/scideberta_SER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="havens2/scideberta_SER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("havens2/scideberta_SER") model = AutoModelForTokenClassification.from_pretrained("havens2/scideberta_SER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7cf3718b9688c78e6773936f80a02846faf7591cb9cc67d9cae65cd1f57ca9d
- Size of remote file:
- 437 MB
- SHA256:
- 3fee99121ebc3b0b26675ee1c35444667fad8e40f83a942e0ea49371a48535f6
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