Instructions to use Laksitha/autotrain-enhanced-tosdr-summariser-1339851272 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Laksitha/autotrain-enhanced-tosdr-summariser-1339851272 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="Laksitha/autotrain-enhanced-tosdr-summariser-1339851272")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Laksitha/autotrain-enhanced-tosdr-summariser-1339851272") model = AutoModelForSeq2SeqLM.from_pretrained("Laksitha/autotrain-enhanced-tosdr-summariser-1339851272") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1339851272
- CO2 Emissions (in grams): 0.0120
Validation Metrics
- Loss: 2.416
- Rouge1: 34.945
- Rouge2: 12.533
- RougeL: 19.876
- RougeLsum: 31.821
- Gen Len: 92.917
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/Laksitha/autotrain-enhanced-tosdr-summariser-1339851272
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