Instructions to use lambdarw/t5_pegasus_ch_ans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lambdarw/t5_pegasus_ch_ans 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="lambdarw/t5_pegasus_ch_ans")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lambdarw/t5_pegasus_ch_ans") model = AutoModelForSeq2SeqLM.from_pretrained("lambdarw/t5_pegasus_ch_ans") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 42285108445
- CO2 Emissions (in grams): 4.4296
Validation Metrics
- Loss: 3.292
- Rouge1: 6.468
- Rouge2: 1.995
- RougeL: 6.485
- RougeLsum: 6.428
- Gen Len: 19.000
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/lambdarw/autotrain-t5-pegasus_ch_ansmrc-42285108445
- Downloads last month
- 8