Instructions to use SEBIS/code_trans_t5_small_program_synthese_transfer_learning_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_small_program_synthese_transfer_learning_finetune 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="SEBIS/code_trans_t5_small_program_synthese_transfer_learning_finetune")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_program_synthese_transfer_learning_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_small_program_synthese_transfer_learning_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Limitations & Biases: Model Card Update (#3)
- Limitations & Biases: Model Card Update (f97f3e35abf5ae248c9829233e15817945036b94) Co-authored-by: Ezi Ozoani <Ezi@users.noreply.huggingface.co>cf3d414
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Model Card (#2)
- Model Card (9b54e427ffd667e3b2836c5545c5b35d308aae96) Co-authored-by: Ezi Ozoani <Ezi@users.noreply.huggingface.co>bdaa33f
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Add TF weights (#1)
- Add TF weights (f12aa344d922bf0aa0fb98efce7eae45dd105425) Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>ff8a875
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