Summarization
Transformers
Safetensors
t5
text2text-generation
politics,
summarization,
climate
political
party,
press
european
text-generation-inference
Instructions to use tdickson17/Text_Summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tdickson17/Text_Summarization 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="tdickson17/Text_Summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tdickson17/Text_Summarization") model = AutoModelForSeq2SeqLM.from_pretrained("tdickson17/Text_Summarization") - Notebooks
- Google Colab
- Kaggle
| <project version="4"> | |
| <component name="Black"> | |
| <option name="sdkName" value="Python 3.11 (cs6601_a0)" /> | |
| </component> | |
| <component name="ProjectRootManager" version="2" project-jdk-name="Palantir_Project" project-jdk-type="Python SDK" /> | |
| </project> |