Summarization
Transformers
PyTorch
Safetensors
English
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use sagard21/python-code-explainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagard21/python-code-explainer 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="sagard21/python-code-explainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sagard21/python-code-explainer") model = AutoModelForSeq2SeqLM.from_pretrained("sagard21/python-code-explainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: I love AutoTrain 🤗
datasets:
- sagard21/autotrain-data-code-explainer
co2_eq_emissions:
emissions: 5.393079045128973
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 2745581349
- CO2 Emissions (in grams): 5.3931
Validation Metrics
- Loss: 2.156
- Rouge1: 29.375
- Rouge2: 18.128
- RougeL: 25.445
- RougeLsum: 28.084
- Gen Len: 19.000
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_HUGGINGFACE_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/sagard21/autotrain-code-explainer-2745581349