Instructions to use MarioBarbeque/CyberSolve-DeepMind-LinAlg-1D-downsample-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarioBarbeque/CyberSolve-DeepMind-LinAlg-1D-downsample-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MarioBarbeque/CyberSolve-DeepMind-LinAlg-1D-downsample-v2") model = AutoModelForSeq2SeqLM.from_pretrained("MarioBarbeque/CyberSolve-DeepMind-LinAlg-1D-downsample-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
A second finetuing of the flan-T5-large model on the downsampled DeepMind LingAlg 1D dataset, this time with a GPU batch size of 256 as opposed to 32 used before
f9ec778 verified - Xet hash:
- 60e440499e0c64afd8c516f152ec2d69fc55a6b52533a74219d47d892571c455
- Size of remote file:
- 3.13 GB
- SHA256:
- c773207658e39642821f177ebb21f2f553badc86cd3881140dc962f099921cc2
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