Token Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use Gayu/my_sequence_labelling_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gayu/my_sequence_labelling_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Gayu/my_sequence_labelling_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Gayu/my_sequence_labelling_model") model = AutoModelForTokenClassification.from_pretrained("Gayu/my_sequence_labelling_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Gayu/my_sequence_labelling_model: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Gayu/my_sequence_labelling_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Gayu/my_sequence_labelling_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Gayu/my_sequence_labelling_model/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- e56d0c5296896ce0751ab59dfcea1e2ca81f286b7cbb98af556037037e1d44c6
- Size of remote file:
- 3.96 kB
- SHA256:
- 9629f3c8a7af00c31cb442102401feab6bc601928e9083a233979d3e331502ac
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