Instructions to use lijingxin/xlm-roberta-base-finetuned-panx-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lijingxin/xlm-roberta-base-finetuned-panx-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="lijingxin/xlm-roberta-base-finetuned-panx-all")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("lijingxin/xlm-roberta-base-finetuned-panx-all") model = AutoModelForTokenClassification.from_pretrained("lijingxin/xlm-roberta-base-finetuned-panx-all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 304eb4b5c72c8749353cbeb8cb60a9d1fd49798a5a6296e3eee5a6fbf642b08e
- Size of remote file:
- 1.11 GB
- SHA256:
- b09fbfb74498b6746257257439e117471dc7be004752a7794e6d5b7487cf6224
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