Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use ethansimrm/test_t5_small_example_kaggle2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethansimrm/test_t5_small_example_kaggle2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ethansimrm/test_t5_small_example_kaggle2") model = AutoModelForSeq2SeqLM.from_pretrained("ethansimrm/test_t5_small_example_kaggle2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ethansimrm/test_t5_small_example_kaggle2: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/ethansimrm/test_t5_small_example_kaggle2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ethansimrm/test_t5_small_example_kaggle2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ethansimrm/test_t5_small_example_kaggle2/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- 8ece63df364811c14904e4c0b893424c884841fa0af4f7b7ed658a0aa2f281c1
- Size of remote file:
- 242 MB
- SHA256:
- 9697018df4502bf2cf67f7e839adf3f914fbaca3104d7a96d83e4c1cc449769f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.