Instructions to use spy24/autonlp-parrot_paraphrasing-615317556 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spy24/autonlp-parrot_paraphrasing-615317556 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("spy24/autonlp-parrot_paraphrasing-615317556") model = AutoModelForMultimodalLM.from_pretrained("spy24/autonlp-parrot_paraphrasing-615317556") - Notebooks
- Google Colab
- Kaggle
metadata
tags: autonlp
language: unk
widget:
- text: I love AutoNLP 🤗
datasets:
- spy24/autonlp-data-parrot_paraphrasing
co2_eq_emissions: 0.8335491678002559
Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 615317556
- CO2 Emissions (in grams): 0.8335491678002559
Validation Metrics
- Loss: 0.0001514342293376103
- Rouge1: 100.0
- Rouge2: 51.4451
- RougeL: 100.0
- RougeLsum: 100.0
- Gen Len: 4.104
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 AutoNLP"}' https://api-inference.huggingface.co/spy24/autonlp-parrot_paraphrasing-615317556