Instructions to use SEBIS/code_trans_t5_base_source_code_summarization_csharp_multitask_finetune 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_multitask_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_base_source_code_summarization_csharp_multitask_finetune")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_source_code_summarization_csharp_multitask_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_base_source_code_summarization_csharp_multitask_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 346 Bytes
64bb8e7 | 1 2 3 4 5 6 7 8 | ---
tags:
- summarization
widget:
- text: "public static DateTime ParseUnixDateTime ( double unixTime ) { var dt = new DateTime ( CODE_INTEGER , CODE_INTEGER , CODE_INTEGER , CODE_INTEGER , CODE_INTEGER , CODE_INTEGER , CODE_INTEGER , System . DateTimeKind . Utc ) ; dt = dt . AddSeconds ( unixTimeStamp ) . ToLocalTime ( ) ; return dt ; }"
---
|