Instructions to use sysresearch101/t5-large-xsum-cnn-8-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sysresearch101/t5-large-xsum-cnn-8-2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sysresearch101/t5-large-xsum-cnn-8-2") model = AutoModelForSeq2SeqLM.from_pretrained("sysresearch101/t5-large-xsum-cnn-8-2") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"model-index[0].results[0].dataset.type" with value "xsum & Cnn" fails to match the required pattern: /^(?:[\w-]+\/)?[\w-.]+$/
language: - en tags: - summarization - t5-large-xsum-cnn-8-2 - pipeline:summarization license: mit model-index: - name: sysresearch101/t5-large-xsum-cnn-8-2" results: - task: type: summarization name: Summarization dataset: name: xsum & Cnn type: xsum & Cnn config: 3.0.0 split: train metrics: - name: ROUGE-1 type: rouge value: verified: true - name: ROUGE-2 type: rouge value: verified: true - name: ROUGE-L type: rouge value: verified: true - name: ROUGE-LSUM type: rouge value: verified: true - name: loss type: loss value: verified: true - name: gen_len type: gen_len value: verified: true
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