Instructions to use ishwarbb23/t5depression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishwarbb23/t5depression with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ishwarbb23/t5depression") model = AutoModelForSeq2SeqLM.from_pretrained("ishwarbb23/t5depression") - Notebooks
- Google Colab
- Kaggle
Commit ·
df1c2eb
1
Parent(s): a81a9ac
t5depression
Browse files- config.json +2 -1
- pytorch_model.bin +1 -1
- training_args.bin +1 -1
config.json
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@@ -1,5 +1,5 @@
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{
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-
"_name_or_path": "t5-
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"architectures": [
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"T5ForConditionalGeneration"
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],
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"dropout_rate": 0.1,
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"eos_token_id": 1,
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"feed_forward_proj": "relu",
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"is_gated_act": false,
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{
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"_name_or_path": "ThomasSimonini/t5-end2end-question-generation",
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"architectures": [
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"T5ForConditionalGeneration"
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],
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"dropout_rate": 0.1,
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"eos_token_id": 1,
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"feed_forward_proj": "relu",
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"gradient_checkpointing": false,
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"is_gated_act": false,
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pytorch_model.bin
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size 891619985
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version https://git-lfs.github.com/spec/v1
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size 891619985
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 4027
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version https://git-lfs.github.com/spec/v1
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size 4027
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