Summarization
Transformers
PyTorch
Safetensors
Enawené-Nawé
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use smirki/autotrain-t5-small-with-big-data-83042142160 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smirki/autotrain-t5-small-with-big-data-83042142160 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="smirki/autotrain-t5-small-with-big-data-83042142160")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("smirki/autotrain-t5-small-with-big-data-83042142160") model = AutoModelForMultimodalLM.from_pretrained("smirki/autotrain-t5-small-with-big-data-83042142160") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 83042142160
- CO2 Emissions (in grams): 1.0227
Validation Metrics
- Loss: 0.027
- Rouge1: 73.911
- Rouge2: 66.528
- RougeL: 73.918
- RougeLsum: 73.889
- 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/smirki/autotrain-t5-small-with-big-data-83042142160
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