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:
- 9970ce5695c47fa3129f43b5110699908a421522a83916e4d2fe0802f9e109e2
- Size of remote file:
- 2.93 kB
- SHA256:
- c43e9cef6b897495a097906680acf3eb904a04b657d43fe0e2e5b6f894e9d613
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.