Instructions to use pradeepiisc/xlm-roberta-base-finetuned-panx-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pradeepiisc/xlm-roberta-base-finetuned-panx-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pradeepiisc/xlm-roberta-base-finetuned-panx-en")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pradeepiisc/xlm-roberta-base-finetuned-panx-en") model = AutoModelForTokenClassification.from_pretrained("pradeepiisc/xlm-roberta-base-finetuned-panx-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b07a0e1c7903204ab1efdf7240555885bcd8523ed643e3447ce75852b3a64c53
- Size of remote file:
- 1.11 GB
- SHA256:
- e85b52bbc44339aab78fb760e60758032ea9e2ddacf9e3781c0e8062115a7a35
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