Instructions to use PanoEvJ/T5_base_SFT_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PanoEvJ/T5_base_SFT_summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PanoEvJ/T5_base_SFT_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("PanoEvJ/T5_base_SFT_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7ac0339486bf06fe5bf97b41d699335031b8a2df5ec51b65c3f64d6b29790d5e
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size 891644832
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