Instructions to use HuyTran1301/constrative_faiss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuyTran1301/constrative_faiss with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("HuyTran1301/constrative_faiss") model = AutoModelForSeq2SeqLM.from_pretrained("HuyTran1301/constrative_faiss") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
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@@ -34,11 +34,11 @@ More information needed
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size:
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 32
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- total_train_batch_size:
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 8
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 24
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 32
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- total_train_batch_size: 768
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 8
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