Instructions to use ativilambit/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ativilambit/results with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ativilambit/results") model = AutoModelForSeq2SeqLM.from_pretrained("ativilambit/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ativilambit/results: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/ativilambit/results/resolve/main/training_args.bin
- Command line
-
hf download hf://ativilambit/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ativilambit/results/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- ef424072038c3c5195ad90420c849f46cc63a8064e3d12043d24bdc4c615c15f
- Size of remote file:
- 4.16 kB
- SHA256:
- 2ab55d472eb5a6e6e9eaff317be264d02920b1f06ae5f500be94a3b5a04b14e5
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