Instructions to use codeaze/deberta_FT_FM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codeaze/deberta_FT_FM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="codeaze/deberta_FT_FM")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("codeaze/deberta_FT_FM") model = AutoModelForTokenClassification.from_pretrained("codeaze/deberta_FT_FM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f28753c7a154dec2572f6b10c9b6d690f11bb46ea30436e371f0c6dc325a4211
- Size of remote file:
- 1.74 GB
- SHA256:
- 9ed5cb7351b17c5eb6cbd60a6923987b055357396276fc0e671741ba496cdc36
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