This model is a fine-tuned version of t5_small on the CNN/Daily Mail dataset
for summarization tasks.
The model was trained on the CNN/Daily Mail dataset.
1from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
2
3tokenizer = AutoTokenizer.from_pretrained("hskang/cnn_dailymail_t5_small")
4model = AutoModelForSeq2SeqLM.from_pretrained("hskang/cnn_dailymail_t5_small")
5
6input_text = "upstage tutorial text summarization code"
7inputs = tokenizer.encode(input_text, return_tensors="pt")
8outputs = model.generate(inputs)
9print(tokenizer.decode(outputs[0], skip_special_tokens=True))
The model may generate biased or inappropriate content due to the nature
of the training data.
It is recommended to use the model with caution and apply necessary filters.
Bias: The model may inherit biases present in the training data.
Misuse: The model can be misused to generate misleading or harmful content.
Copyright and License
This model is licensed under the MIT License.
