Token Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune") model = AutoModelForTokenClassification.from_pretrained("swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune/resolve/main/training_args.bin
- Command line
-
hf download hf://swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/swtb/XLM-RoBERTa-Base-Conll2003-English-NER-Finetune/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- c2e6099fafbc9dd92571150e37e870cef890f82663731c310a70f4dcf9538c0c
- Size of remote file:
- 5.11 kB
- SHA256:
- b8019bfb333859c35ba57408d14f7607c5e781813bfbf19f8be83f446a1ac02e
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