Summarization
Transformers
PyTorch
English
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use KoddaDuck/Cylonix_text_sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoddaDuck/Cylonix_text_sum 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="KoddaDuck/Cylonix_text_sum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KoddaDuck/Cylonix_text_sum") model = AutoModelForSeq2SeqLM.from_pretrained("KoddaDuck/Cylonix_text_sum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e14f4a478de29eb4aed2b586d6e644b8b3c39603f072dd4d4dd38609abe51ae0
- Size of remote file:
- 2.42 MB
- SHA256:
- 325982f929fb03e41968f4c0cdee41fa6d0cff2f6e15393ff2c72aec979a09fb
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