Instructions to use omar47/t5-base-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omar47/t5-base-summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("omar47/t5-base-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("omar47/t5-base-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.13b68d8
-
Upload tokenizer
e150104 -
Upload tokenizer
d51fb8e -
Upload tokenizer
81f183e -
Upload T5ForConditionalGeneration
d43c1df -
Upload tokenizer
1c8831c
-
Upload T5ForConditionalGeneration
356763e -
Upload tokenizer
905979f -
Upload tokenizer
3956bd0 -
Upload tokenizer
a1ea054 -
Upload tokenizer
e62d490 -
Upload tokenizer
d463e77 -
Upload T5ForConditionalGeneration
ce64926 -
Upload tokenizer
3ebc590 -
Upload tokenizer
8c2f4ee -
Upload tokenizer
feb5800 -
Upload tokenizer
f410c12
-
Upload T5ForConditionalGeneration
e314793 -
initial commit
00bd6be