Instructions to use ldenoue/Title_Generation_T5Small_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ldenoue/Title_Generation_T5Small_Model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ldenoue/Title_Generation_T5Small_Model") model = AutoModelForSeq2SeqLM.from_pretrained("ldenoue/Title_Generation_T5Small_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_model_quantized.onnx from ldenoue/Title_Generation_T5Small_Model: direct link, hf CLI and curl.
- Browser
- Download file 42.2 MB
-
https://huggingface.co/ldenoue/Title_Generation_T5Small_Model/resolve/main/onnx/decoder_model_quantized.onnx
- Command line
-
hf download hf://ldenoue/Title_Generation_T5Small_Model/onnx/decoder_model_quantized.onnx
-
curl -L -o decoder_model_quantized.onnx https://huggingface.co/ldenoue/Title_Generation_T5Small_Model/resolve/main/onnx/decoder_model_quantized.onnx
42.2 MB
- Xet hash:
- 7c1bf62897f299b36ccec122a54704b7e8d4d64712dc1b8fdf844996d4f8ad8f
- Size of remote file:
- 42.2 MB
- SHA256:
- 4bc4b0ea922270e92ade0e59c6e397063cffa3c91923604d8d15f36cd2a5463a
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