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:
- 5f51d146241dc109bd70c72c26d8736753d5cd28a82787a5dd9f9f5573fcb646
- Size of remote file:
- 2.24 GB
- SHA256:
- 092cd77e2929ec9764f95ae12b092504006f6e5765cac0cf633a3b5b4af3b17a
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