Instructions to use SEBIS/code_trans_t5_small_source_code_summarization_python_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_source_code_summarization_python_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_source_code_summarization_python_transfer_learning_finetune")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_source_code_summarization_python_transfer_learning_finetune") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_small_source_code_summarization_python_transfer_learning_finetune") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -1,9 +1,12 @@
|
|
| 1 |
---
|
|
|
|
| 2 |
tags:
|
| 3 |
- summarization
|
| 4 |
widget:
|
| 5 |
-
- text: '''with open ( CODE_STRING , CODE_STRING ) as in_file : buf = in_file . readlines
|
| 6 |
-
|
|
|
|
|
|
|
| 7 |
---
|
| 8 |
|
| 9 |
|
|
|
|
| 1 |
---
|
| 2 |
+
language: code
|
| 3 |
tags:
|
| 4 |
- summarization
|
| 5 |
widget:
|
| 6 |
+
- text: '''with open ( CODE_STRING , CODE_STRING ) as in_file : buf = in_file . readlines
|
| 7 |
+
( ) with open ( CODE_STRING , CODE_STRING ) as out_file : for line in buf : if
|
| 8 |
+
line == " ; Include this text " : line = line + " Include below " out_file
|
| 9 |
+
. write ( line ) '''
|
| 10 |
---
|
| 11 |
|
| 12 |
|