Instructions to use Brendan/meta-baseline-t5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Brendan/meta-baseline-t5-small with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Brendan/meta-baseline-t5-small") model = AutoModelForSeq2SeqLM.from_pretrained("Brendan/meta-baseline-t5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c00c1c6c850b8251cbc04486eb456fbb8166f6023af9ecacba3bd58f2e93faf
- Size of remote file:
- 242 MB
- SHA256:
- 39532ac1e4e8582f0156112f0cd1500f0df047301b609fdc4bdc9229b62ba8fc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.