Instructions to use nbroad/mt5-base-qgen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/mt5-base-qgen with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nbroad/mt5-base-qgen") model = AutoModelForSeq2SeqLM.from_pretrained("nbroad/mt5-base-qgen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (4c3dd473fa37f0f0c85f1e74b25d3f256278797e) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>437fbfc
-
Add multilingual to the language tag (#1)
- Add multilingual to the language tag (9dd7479ead5460b3aa40a822fa8d59c741e3c616) - Fix non-ascii characters (e39503b57ed31884e3e77798afb4d41fcfd3dbba) Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>d07de81
-
Update README.md
9b215a0 -
add pt and tf weights
EC2 Default User7bf04d9
-
Update README.md
71c6fde -
Update README.md
9e14b8f -
Update ReadMe with dataset info
fec6f45
-
Create README.md
69cc4ea
-
Saving weights and logs of epoch 2
0d6963d -
Saving weights and logs of epoch 1
96e31eb -
Saving weights and logs of epoch 0
27d3ea5
-
Upload run_summarization_flax.py
ab87e85 -
Upload start_qgen.sh
1c58869 -
Upload start_qgen.sh
b6be418 -
Upload run_summarization_flax.py
e3b3f1e -
initial commit
caafc9c