Instructions to use Ayham/xlmroberta_gpt2_summarization_xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayham/xlmroberta_gpt2_summarization_xsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ayham/xlmroberta_gpt2_summarization_xsum") model = AutoModelForSeq2SeqLM.from_pretrained("Ayham/xlmroberta_gpt2_summarization_xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82a9c3ea8534aaecbbeeb222a4ca60fd361441a95c7b9123e74c132d1e7facbc
- Size of remote file:
- 1.75 GB
- SHA256:
- 1042aab0c03355525cad5820ef27faa52555ee1209852e851dba40e3e7801511
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