Instructions to use LSimmons/FragZONFactMetaRecommendationHyperParamSearch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LSimmons/FragZONFactMetaRecommendationHyperParamSearch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LSimmons/FragZONFactMetaRecommendationHyperParamSearch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LSimmons/FragZONFactMetaRecommendationHyperParamSearch") model = AutoModelForSequenceClassification.from_pretrained("LSimmons/FragZONFactMetaRecommendationHyperParamSearch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LSimmons/FragZONFactMetaRecommendationHyperParamSearch: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/LSimmons/FragZONFactMetaRecommendationHyperParamSearch/resolve/main/training_args.bin
- Command line
-
hf download hf://LSimmons/FragZONFactMetaRecommendationHyperParamSearch/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/LSimmons/FragZONFactMetaRecommendationHyperParamSearch/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 20d7a8dc613a76e8f67522328f5f65aefbbaa746dcc6dd9cb1d5d31458acccf3
- Size of remote file:
- 4.6 kB
- SHA256:
- 028ba73a79820593d7ae4350917a320b45c393de76ffd6423f85450f36854e6b
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