Instructions to use Erdenebold/testing_mongolian-roberta_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Erdenebold/testing_mongolian-roberta_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Erdenebold/testing_mongolian-roberta_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Erdenebold/testing_mongolian-roberta_base") model = AutoModelForTokenClassification.from_pretrained("Erdenebold/testing_mongolian-roberta_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Erdenebold/testing_mongolian-roberta_base: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/Erdenebold/testing_mongolian-roberta_base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Erdenebold/testing_mongolian-roberta_base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Erdenebold/testing_mongolian-roberta_base/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- be5954f4b272a5581075efbd22ed5567546b4983e08b85564a72979c89bf304a
- Size of remote file:
- 496 MB
- SHA256:
- acc3bde1b1e2dc2810545cb5b105d5e8c185ceaa6481eb4ed420d1ff23863ecc
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