Summarization
Transformers
PyTorch
TensorBoard
Safetensors
English
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use sudoLife/tst-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sudoLife/tst-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="sudoLife/tst-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sudoLife/tst-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("sudoLife/tst-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d23c41885f19c96fe518bfa864a89532221641b44d7eb2e83dd9b17fccf8e5e
- Size of remote file:
- 242 MB
- SHA256:
- caf284a74e616210426a66923213de8d7b13df734a10abe835e5236682706f53
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