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:
- a3528e4bea5a33dd44eff8a003fef59e13c8fdac13ca2b637210abfdaaf6c936
- Size of remote file:
- 436 MB
- SHA256:
- 8b196b1c9ff3568d9b09563e517060228b04aa8d0f4f1bb6b21ffb2d138de73e
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