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/encoder_model_quantized.onnx from ldenoue/Title_Generation_T5Small_Model: direct link, hf CLI and curl.
- Browser
- Download file 35.6 MB
-
https://huggingface.co/ldenoue/Title_Generation_T5Small_Model/resolve/main/onnx/encoder_model_quantized.onnx
- Command line
-
hf download hf://ldenoue/Title_Generation_T5Small_Model/onnx/encoder_model_quantized.onnx
-
curl -L -o encoder_model_quantized.onnx https://huggingface.co/ldenoue/Title_Generation_T5Small_Model/resolve/main/onnx/encoder_model_quantized.onnx
35.6 MB
- Xet hash:
- bea89e4af864e78737935ce38bad3217f0f2ebd5fe8e286721c629ccf39d21e5
- Size of remote file:
- 35.6 MB
- SHA256:
- fedd30e8d3dbb8832255d80dc5c64851a72387a56381cd098464c06c4c981827
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