Instructions to use mrm8488/t5-base-finetuned-tab_fact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/t5-base-finetuned-tab_fact with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-tab_fact") model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/t5-base-finetuned-tab_fact", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e20174207e9bc65bfead074fafed7a880d6db01f31086857a52afaa45fed303
- Size of remote file:
- 74.1 MB
- SHA256:
- 12d4771bebfc8ffa6b3ad159ab7a53a0112d73a8cac50f7b7961b3cab554acd2
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