Instructions to use nizamudma/bart_cnn_auto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nizamudma/bart_cnn_auto with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nizamudma/bart_cnn_auto") model = AutoModelForSeq2SeqLM.from_pretrained("nizamudma/bart_cnn_auto") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"tags" must be an array
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1046236000
- CO2 Emissions (in grams): 4581.794954519826
Validation Metrics
- Loss: 1.4225560426712036
- Rouge1: 42.5931
- Rouge2: 20.0106
- RougeL: 29.681
- RougeLsum: 39.8097
- Gen Len: 84.9844
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/nizamudma/autotrain-text1-1046236000
- Downloads last month
- -
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support