Token Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use swtb/encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swtb/encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="swtb/encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("swtb/encoder") model = AutoModelForTokenClassification.from_pretrained("swtb/encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 118f1fb49755c721e4a21e6d5c4959ad1de45220474b6be436f4e02d6e30509c
- Size of remote file:
- 5.18 kB
- SHA256:
- d6581b5bc4fcb15a5614c632eca21ae3b29ac1dd547ffb0b6dc43a0b0c2b6f64
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