Instructions to use mrwolf883/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrwolf883/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrwolf883/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrwolf883/results") model = AutoModelForSequenceClassification.from_pretrained("mrwolf883/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mrwolf883/results: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/mrwolf883/results/resolve/main/training_args.bin
- Command line
-
hf download hf://mrwolf883/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mrwolf883/results/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 46980cb5e4c126e620df88b83607f94eadf0a51b4d53a00505303dfbd5eb0a6f
- Size of remote file:
- 5.2 kB
- SHA256:
- a7d4f3f97985772b0a02c47c515478f009d2422199d34afce7b519b6ffef560a
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