Summarization
Transformers
PyTorch
English
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use ishajo/meeting_summarization_usingT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishajo/meeting_summarization_usingT5 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="ishajo/meeting_summarization_usingT5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ishajo/meeting_summarization_usingT5") model = AutoModelForSeq2SeqLM.from_pretrained("ishajo/meeting_summarization_usingT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 767 Bytes
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tags:
- autotrain
- summarization
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- ishajo/autotrain-data-beproj_meeting_summarization_usingt5
co2_eq_emissions:
emissions: 5.143894810258375
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 49444119397
- CO2 Emissions (in grams): 5.1439
## Validation Metrics
- Loss: 1.516
- Rouge1: 25.859
- Rouge2: 12.703
- RougeL: 21.352
- RougeLsum: 24.239
- Gen Len: 18.995
## 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/ishajo/autotrain-beproj_meeting_summarization_usingt5-49444119397
``` |