Instructions to use BramVanroy/deberta-v3-base-uner-down-synth400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BramVanroy/deberta-v3-base-uner-down-synth400 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BramVanroy/deberta-v3-base-uner-down-synth400")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BramVanroy/deberta-v3-base-uner-down-synth400") model = AutoModelForTokenClassification.from_pretrained("BramVanroy/deberta-v3-base-uner-down-synth400", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42ee7c76a2bc3fcb0421103427d9be92be38749bbc2018e8694ec4f8d84cd9fd
- Size of remote file:
- 5.84 kB
- SHA256:
- 37eeb8057cba6730c98f00c94befea9a46ec65ce5bb0e690580b03a0018b0ea0
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