Instructions to use mh01/multilingual-e5-base_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mh01/multilingual-e5-base_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mh01/multilingual-e5-base_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mh01/multilingual-e5-base_ner") model = AutoModelForSequenceClassification.from_pretrained("mh01/multilingual-e5-base_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0ac47aadd885b9bd4b8ec133d62ea00c5ee3133db437fe0d1b13ab62c3a5159
- Size of remote file:
- 5.18 kB
- SHA256:
- 8043a32b7b0e630f04faf2a664ca9042d069d54cc3cb16355081a67d857ae1d0
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