Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use milyiyo/stog-t5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use milyiyo/stog-t5-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("milyiyo/stog-t5-small") model = AutoModelForSeq2SeqLM.from_pretrained("milyiyo/stog-t5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from milyiyo/stog-t5-small: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/milyiyo/stog-t5-small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://milyiyo/stog-t5-small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/milyiyo/stog-t5-small/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- c1e953e63d29cc409744801ddefedd8f369d80415c8e885b28c2a7994cc6575b
- Size of remote file:
- 242 MB
- SHA256:
- 2db7d3c5d6b9fbfc784f4f6a8caba338179e9d710ce129585b0a4b9f330a8f7c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.