Instructions to use Mia2024/CS5100TextSummarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mia2024/CS5100TextSummarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Mia2024/CS5100TextSummarization") model = AutoModelForSeq2SeqLM.from_pretrained("Mia2024/CS5100TextSummarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload BartForConditionalGeneration
Browse files- adapter_config.json +2 -2
adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"task_type": "SEQ_2_SEQ_LM",
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"use_dora": false,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"task_type": "SEQ_2_SEQ_LM",
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"use_dora": false,
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