Instructions to use ktgiahieu/RoBERTa-large-PM-M3-Voc-hf-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ktgiahieu/RoBERTa-large-PM-M3-Voc-hf-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ktgiahieu/RoBERTa-large-PM-M3-Voc-hf-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ktgiahieu/RoBERTa-large-PM-M3-Voc-hf-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("ktgiahieu/RoBERTa-large-PM-M3-Voc-hf-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f71fa7005a31cb46f47fbc6b7394bf88a27cbd3d90d2a17d4ceaa35668ad2a66
- Size of remote file:
- 3.64 kB
- SHA256:
- 519718ddb28414812fe76b3459c000d4e912fc33ecbb909d5e671918d1bcebaa
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