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
|
Download README.md from ishajo/meeting_summarization_usingT5: direct link, hf CLI and curl.
- Browser
- Download file 767 Bytes
-
https://huggingface.co/ishajo/meeting_summarization_usingT5/resolve/main/README.md
- Command line
-
hf download hf://ishajo/meeting_summarization_usingT5/README.md
-
curl -L -o README.md https://huggingface.co/ishajo/meeting_summarization_usingT5/resolve/main/README.md
767 Bytes
| 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 | |
| ``` |