Summarization
Transformers
PyTorch
English
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use lightbansal/autotrain-metadata_postprocess-1277848897 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lightbansal/autotrain-metadata_postprocess-1277848897 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="lightbansal/autotrain-metadata_postprocess-1277848897")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lightbansal/autotrain-metadata_postprocess-1277848897") model = AutoModelForSeq2SeqLM.from_pretrained("lightbansal/autotrain-metadata_postprocess-1277848897", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - autotrain | |
| - summarization | |
| language: | |
| - en | |
| widget: | |
| - text: "I love AutoTrain 🤗" | |
| datasets: | |
| - lightbansal/autotrain-data-metadata_postprocess | |
| co2_eq_emissions: | |
| emissions: 0.5973129947175277 | |
| # Model Trained Using AutoTrain | |
| - Problem type: Summarization | |
| - Model ID: 1277848897 | |
| - CO2 Emissions (in grams): 0.5973 | |
| ## Validation Metrics | |
| - Loss: 0.198 | |
| - Rouge1: 94.055 | |
| - Rouge2: 30.091 | |
| - RougeL: 93.235 | |
| - RougeLsum: 93.269 | |
| - Gen Len: 4.493 | |
| ## 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/lightbansal/autotrain-metadata_postprocess-1277848897 | |
| ``` |