Instructions to use APredator/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use APredator/results with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("APredator/results") model = AutoModelForSeq2SeqLM.from_pretrained("APredator/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from APredator/results: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/APredator/results/resolve/main/training_args.bin
- Command line
-
hf download hf://APredator/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/APredator/results/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 4d719b99cf94e10068c310e00431b5f8447d207eab1a1e1283c167575e071314
- Size of remote file:
- 5.24 kB
- SHA256:
- 027c414f8c99440e4d14c3efeaa54dcdeebd72e6ee4d26bb104f62bffc2cf334
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