Instructions to use Udit191/autotrain-summarization-bart-50017120109 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Udit191/autotrain-summarization-bart-50017120109 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="Udit191/autotrain-summarization-bart-50017120109")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Udit191/autotrain-summarization-bart-50017120109") model = AutoModelForSeq2SeqLM.from_pretrained("Udit191/autotrain-summarization-bart-50017120109") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 50017120109
- CO2 Emissions (in grams): 0.0055
Validation Metrics
- Loss: 2.538
- Rouge1: 49.903
- Rouge2: 20.621
- RougeL: 27.927
- RougeLsum: 44.133
- Gen Len: 142.000
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/Udit191/autotrain-summarization-bart-50017120109
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