Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use shivaneej/subset_model_flan_t5_html with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shivaneej/subset_model_flan_t5_html with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shivaneej/subset_model_flan_t5_html") model = AutoModelForSeq2SeqLM.from_pretrained("shivaneej/subset_model_flan_t5_html", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c350502819186e6af4a64ee224f52c2f3aefb32ed31e4c51339106e3b9cc9627
- Size of remote file:
- 308 MB
- SHA256:
- d11d45f5d5e529e57c24a7a2454d860c50aae608b31be38e180cab72d05f4442
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.