Instructions to use akshara23/summarization_model_save with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akshara23/summarization_model_save with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("akshara23/summarization_model_save") model = AutoModelForSeq2SeqLM.from_pretrained("akshara23/summarization_model_save", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from akshara23/summarization_model_save: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/akshara23/summarization_model_save/resolve/main/tf_model.h5
- Command line
-
hf download hf://akshara23/summarization_model_save/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/akshara23/summarization_model_save/resolve/main/tf_model.h5
242 MB
- Xet hash:
- fdcb57c9c6c7b14fc2f16b771d76df193766a4bd194e5cb588ad45aba7ac8edd
- Size of remote file:
- 242 MB
- SHA256:
- 8d3faaaf7e715d9aff8353645e32d2613b449a322611d114394e67672e80dd06
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