Instructions to use namin0202/pna-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namin0202/pna-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="namin0202/pna-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("namin0202/pna-roberta-large") model = AutoModel.from_pretrained("namin0202/pna-roberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from namin0202/pna-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 2.1 kB
-
https://huggingface.co/namin0202/pna-roberta-large/resolve/main/training_args.bin
- Command line
-
hf download hf://namin0202/pna-roberta-large/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/namin0202/pna-roberta-large/resolve/main/training_args.bin
2.1 kB
- Xet hash:
- 64457d3c0071c99df365bed556b3b9f757c28fb1c0d9a6d510642fe05968bf94
- Size of remote file:
- 2.1 kB
- SHA256:
- ff6a5c4fd55a7a40f4a9472d9699eed64fd80002ecd350f4ea5366a92207f9ab
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