Instructions to use Dhrumit1314/BART_TextSummary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dhrumit1314/BART_TextSummary with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Dhrumit1314/BART_TextSummary") model = AutoModelForSeq2SeqLM.from_pretrained("Dhrumit1314/BART_TextSummary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -2
config.json
CHANGED
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@@ -50,8 +50,8 @@
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"task_specific_params": {
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"summarization": {
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"length_penalty": 1.0,
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"max_length":
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"min_length":
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"num_beams": 4
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},
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"summarization_cnn": {
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"task_specific_params": {
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"summarization": {
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"length_penalty": 1.0,
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"max_length": 512,
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"min_length": 256,
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"num_beams": 4
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},
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"summarization_cnn": {
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