Instructions to use AnanthZeke/tabert-4k-naamapadam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnanthZeke/tabert-4k-naamapadam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AnanthZeke/tabert-4k-naamapadam")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AnanthZeke/tabert-4k-naamapadam") model = AutoModelForTokenClassification.from_pretrained("AnanthZeke/tabert-4k-naamapadam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f72b11b79157a4ab74399d34f9b5e44c92b6ea56aec5419fd3a57d57ec2d5ede
- Size of remote file:
- 3.96 kB
- SHA256:
- 0592fbc5b5feadd43b1efdca2de1049f02f1d89061e641754212d41b051b7eb9
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