Instructions to use valurank/headline_generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use valurank/headline_generator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("valurank/headline_generator") model = AutoModelForSeq2SeqLM.from_pretrained("valurank/headline_generator", 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.4b16bd3
-
Update README.md
d7f8231
-
Update README.md
c9a4f7e -
Update README.md
fc1f580
-
Update README.md
55ed729 -
Create new file
7186485
-
update model card README.md
506ab61 -
Training complete!
51677e4 -
initial commit
44b9577