Instructions to use nuguri01/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nuguri01/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nuguri01/ynat-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nuguri01/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("nuguri01/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nuguri01/ynat-model: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/nuguri01/ynat-model/resolve/main/training_args.bin
- Command line
-
hf download hf://nuguri01/ynat-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nuguri01/ynat-model/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 928b742dd7b0e0f95da868fbb0224fa5d5b1478d80faada3cb15ce5d8470fdd1
- Size of remote file:
- 5.3 kB
- SHA256:
- 5411348c8737f71469937ed67756350b609b7216e8567cca79eabd14013dbb35
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