Summarization
Transformers
PyTorch
Enawené-Nawé
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use rosetta/summarization_trial_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rosetta/summarization_trial_model 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="rosetta/summarization_trial_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rosetta/summarization_trial_model") model = AutoModelForSeq2SeqLM.from_pretrained("rosetta/summarization_trial_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - autotrain | |
| - summarization | |
| language: | |
| - unk | |
| widget: | |
| - text: "I love AutoTrain 🤗" | |
| datasets: | |
| - rosettastone/autotrain-data-summarization-trial | |
| co2_eq_emissions: | |
| emissions: 1116.1106035336509 | |
| # Model Trained Using AutoTrain | |
| - Problem type: Summarization | |
| - Model ID: 1354552136 | |
| - CO2 Emissions (in grams): 1116.1106 | |
| ## Validation Metrics | |
| - Loss: 1.802 | |
| - Rouge1: 21.282 | |
| - Rouge2: 9.419 | |
| - RougeL: 18.171 | |
| - RougeLsum: 19.173 | |
| - Gen Len: 18.954 | |
| ## 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/rosettastone/autotrain-summarization-trial-1354552136 | |
| ``` |