Instructions to use SEBIS/code_trans_t5_base_source_code_summarization_csharp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_base_source_code_summarization_csharp 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_base_source_code_summarization_csharp")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_source_code_summarization_csharp") model = AutoModelForMultimodalLM.from_pretrained("SEBIS/code_trans_t5_base_source_code_summarization_csharp") - Notebooks
- Google Colab
- Kaggle
Commit ·
941cc11
1
Parent(s): 3c2cb6c
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:2036102e3ecaeb417659d2114f19313530544a6bf33547a6713ae2426680f9b2
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size 891625348
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