Instructions to use Ayham/albert_gpt2_summarization_xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayham/albert_gpt2_summarization_xsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ayham/albert_gpt2_summarization_xsum") model = AutoModelForSeq2SeqLM.from_pretrained("Ayham/albert_gpt2_summarization_xsum") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e80d9493958189a0add616351c3391dba356e52472af96ea5460a1038a164534
- Size of remote file:
- 2.99 kB
- SHA256:
- 86dd1bab9763aed7b8d89fedc9623906a3b8c15d09a35e914f782a6ce5fc95c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.