Instructions to use JackBAI/query_decision_train_on_maybe_valid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JackBAI/query_decision_train_on_maybe_valid with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JackBAI/query_decision_train_on_maybe_valid") model = AutoModelForSeq2SeqLM.from_pretrained("JackBAI/query_decision_train_on_maybe_valid") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a3f989d0555df50f9e204a0333b514b917a9ea560e08c08990433bae0e3eb6a
- Size of remote file:
- 990 MB
- SHA256:
- bc0b7b0031332febe6d668171f9a224f03725fcbaedc0ab011705099ee073281
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.