Instructions to use projecte-aina/multiner_ceil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use projecte-aina/multiner_ceil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="projecte-aina/multiner_ceil")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/multiner_ceil") model = AutoModelForTokenClassification.from_pretrained("projecte-aina/multiner_ceil") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80e730f84ba83738f360e3e998f8ebadd1aab2479e1af066c5fd9f7310da1d57
- Size of remote file:
- 1.42 GB
- SHA256:
- 548169d39b0c65631316f07874edd69845c3bf7b006fd39cdb06924873784275
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