Instructions to use frostbyte012/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frostbyte012/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="frostbyte012/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("frostbyte012/results") model = AutoModelForSequenceClassification.from_pretrained("frostbyte012/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from frostbyte012/results: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/frostbyte012/results/resolve/main/training_args.bin
- Command line
-
hf download hf://frostbyte012/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/frostbyte012/results/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 540116706b120aa33232c7a3191679c93095661cce314f1f6b0712f309b8c80e
- Size of remote file:
- 5.24 kB
- SHA256:
- 4c82cc4665b5b1649ba3fe366ff8cadee856418efee53bcc2103931e88f381ed
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