Instructions to use nlpso/m1_ind_layers_ref_ptrn_cmbert_io_level_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpso/m1_ind_layers_ref_ptrn_cmbert_io_level_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nlpso/m1_ind_layers_ref_ptrn_cmbert_io_level_1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nlpso/m1_ind_layers_ref_ptrn_cmbert_io_level_1") model = AutoModelForTokenClassification.from_pretrained("nlpso/m1_ind_layers_ref_ptrn_cmbert_io_level_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 278b4d8412d9ad6a58fdcfe76a51474022129a580013f04fdac32a103223003b
- Size of remote file:
- 14.5 kB
- SHA256:
- 2bdf20939e1cdf8f649931ba045a15cb450b1364a27c1550cd205e8d62b56b8d
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