Instructions to use OTAR3088/CeLLaTe_V3.3_downsampled_lr-2.353 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OTAR3088/CeLLaTe_V3.3_downsampled_lr-2.353 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OTAR3088/CeLLaTe_V3.3_downsampled_lr-2.353")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OTAR3088/CeLLaTe_V3.3_downsampled_lr-2.353") model = AutoModelForTokenClassification.from_pretrained("OTAR3088/CeLLaTe_V3.3_downsampled_lr-2.353") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8aac85f559ee19cde7b52f6581348172e8c345216617575f4c01b3ead5af0b99
- Size of remote file:
- 440 MB
- SHA256:
- 1f38d443e3af1e6e6f4c0784c14a56dc8346627b4c9c417a30593d88c86b22bf
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