Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Randomui/finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Randomui/finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Randomui/finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Randomui/finetuned") model = AutoModelForTokenClassification.from_pretrained("Randomui/finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9670e5fdf0ff6cae22441387238d5793c0c34d5afbd6dfd043e0a44f598dd2f3
- Size of remote file:
- 3.52 kB
- SHA256:
- 8f156dbd84fa64bf064bc37abfbeeb361f956309cfc1fa8fd7567bdb28118f37
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