Instructions to use aseifert/comma-mdeberta-v3-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aseifert/comma-mdeberta-v3-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aseifert/comma-mdeberta-v3-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aseifert/comma-mdeberta-v3-base") model = AutoModelForTokenClassification.from_pretrained("aseifert/comma-mdeberta-v3-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0571d479d81aa252aebf31e7b9de0b2b043a6ffe294ddffb96c917fcc8f018c1
- Size of remote file:
- 1.11 GB
- SHA256:
- 49997f9e2ed449dbb2c71eea85988c0f1ec0f564e563baeb55178bd2df4773b1
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