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:
- 8447d88848bdc1390ca30caaba962575e60343de23e510aa7a28d78e824a31eb
- Size of remote file:
- 2.95 GB
- SHA256:
- cb0aa42bd49fa8cd344a028e7ced1d7c1919e554b096cfb047c92428967a9a26
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