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
File size: 726 Bytes
633ef02 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | ---
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
``` |