Instructions to use mamei16/chonky_distilbert-base-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mamei16/chonky_distilbert-base-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mamei16/chonky_distilbert-base-multilingual-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mamei16/chonky_distilbert-base-multilingual-cased") model = AutoModelForTokenClassification.from_pretrained("mamei16/chonky_distilbert-base-multilingual-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 391f75ac78126d223d5f652d173f39a93ed0965b45a34a2f46d51cdea30f93ea
- Size of remote file:
- 539 MB
- SHA256:
- 030a3c7aa5dd75c18db8cbf3cca1c521776d716f3a99a05513c0e624ae9a4600
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