Summarization
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
Trained with AutoTrain
Instructions to use AyoubChLin/test-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyoubChLin/test-summarizer 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="AyoubChLin/test-summarizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/test-summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("AyoubChLin/test-summarizer") - Notebooks
- Google Colab
- Kaggle
File size: 725 Bytes
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tags:
- autotrain
- summarization
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- AyoubChLin/autotrain-data-test-summar
co2_eq_emissions:
emissions: 2.455344885916781
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 49822119902
- CO2 Emissions (in grams): 2.4553
## Validation Metrics
- Loss: 1.549
- Rouge1: 46.577
- Rouge2: 23.864
- RougeL: 39.450
- RougeLsum: 43.295
- Gen Len: 18.515
## 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/AyoubChLin/autotrain-test-summar-49822119902
``` |