Summarization
Transformers
PyTorch
Safetensors
English
t5
text2text-generation
t5-small
medical-research
text-generation-inference
Instructions to use TusharJoshi89/title-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TusharJoshi89/title-generator with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="TusharJoshi89/title-generator")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("TusharJoshi89/title-generator") model = AutoModelForSeq2SeqLM.from_pretrained("TusharJoshi89/title-generator") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
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.
TusharJoshi89 changed pull request status to merged