Instructions to use dtorber/BioNLP-intro-disc-tech-decoder-PLOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-intro-disc-tech-decoder-PLOS 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="dtorber/BioNLP-intro-disc-tech-decoder-PLOS")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-tech-decoder-PLOS") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-tech-decoder-PLOS") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +1 -1
- model.safetensors +1 -1
- training_args.bin +2 -2
config.json
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"num_hidden_layers": 6,
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"pad_token_id": 1,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 50272
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}
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"num_hidden_layers": 6,
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"pad_token_id": 1,
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"use_cache": true,
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"vocab_size": 50272
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}
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model.safetensors
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training_args.bin
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size 4347
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