Summarization
Transformers
PyTorch
English
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use ashwinR/CodeExplainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashwinR/CodeExplainer 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="ashwinR/CodeExplainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ashwinR/CodeExplainer") model = AutoModelForSeq2SeqLM.from_pretrained("ashwinR/CodeExplainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88ff15c8e1a311243056993f30b72ff5e96069f983889c27ebd1e4f52f69d4ae
- Size of remote file:
- 2.95 GB
- SHA256:
- e8eaf24cf06354f8adf76f137f0319cfb618cfd2abb19496c94fd3d3a9e08404
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