Instructions to use sshleifer/student_xsum_3_12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/student_xsum_3_12 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/student_xsum_3_12") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/student_xsum_3_12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a3285d27a2f715bf4fc6dfa9abbd6d822b59e810744eeb7b7340d16dc8ab9bf
- Size of remote file:
- 1.17 GB
- SHA256:
- 021dc074a5fbcc65618bef9ee87fb961442436872d42c42bfb49c8ed8149ffa6
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