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
- Xet hash:
- 47822d3e28c4eb670bdca3fb77f600d18e0ab2fbfc9cdf403a06d604f1491177
- Size of remote file:
- 627 Bytes
- SHA256:
- 2b3b2a129639e4a3c47b487288feb3a58ca2794ba7ae74d20499bbe0637078b4
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