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")# 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") - Notebooks
- Google Colab
- Kaggle
Commit ·
ff8a875
1
Parent(s): 251beaa
Add TF weights (#1)
Browse files- Add TF weights (f12aa344d922bf0aa0fb98efce7eae45dd105425)
Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:dc37a5110a4c1d57533d85d88873da717172d8aca63547a782846050b0c36bb8
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size 242297600
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