Instructions to use mudes/multilingual-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mudes/multilingual-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mudes/multilingual-large")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mudes/multilingual-large") model = AutoModelForTokenClassification.from_pretrained("mudes/multilingual-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mudes/multilingual-large: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/mudes/multilingual-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mudes/multilingual-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mudes/multilingual-large/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- ea3dbc5cdd421e3aa6d68d3037329fe39f660385861ce873e1e694b360b9c62b
- Size of remote file:
- 2.24 GB
- SHA256:
- 491ea56558b0288f3b1fad1ebb1af8f362f01be4bf0bb5435f94cdc3b0e28a3d
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