Instructions to use Anorak/nirvana with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anorak/nirvana with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Anorak/nirvana") model = AutoModelForSeq2SeqLM.from_pretrained("Anorak/nirvana", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: autonlp | |
| language: unk | |
| widget: | |
| - text: "I love AutoNLP 🤗" | |
| datasets: | |
| - Anorak/autonlp-data-Niravana-test2 | |
| co2_eq_emissions: 4.214012748213151 | |
| # Model Trained Using AutoNLP | |
| - Problem type: Summarization | |
| - Model ID: 20384195 | |
| - CO2 Emissions (in grams): 4.214012748213151 | |
| ## Validation Metrics | |
| - Loss: 1.0120062828063965 | |
| - Rouge1: 41.1808 | |
| - Rouge2: 26.2564 | |
| - RougeL: 31.3106 | |
| - RougeLsum: 38.9991 | |
| - Gen Len: 58.45 | |
| ## 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/Anorak/autonlp-Niravana-test2-20384195 | |
| ``` |