Instructions to use Valencio/LLM_course_EncDec_model_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Valencio/LLM_course_EncDec_model_summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Valencio/LLM_course_EncDec_model_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Valencio/LLM_course_EncDec_model_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98ae225410596c4ecc7797dc339360feb60b73081921d0245376313874ff3964
- Size of remote file:
- 5.33 kB
- SHA256:
- a27a80fcf2ac5d044b27e0c1d9fda29f03e9f9c97511860b14ab66b5867a6602
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