Summarization
Transformers
PyTorch
Enawené-Nawé
blenderbot
text2text-generation
Trained with AutoTrain
Instructions to use breadlicker45/autotrain-blender-50601120822 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use breadlicker45/autotrain-blender-50601120822 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="breadlicker45/autotrain-blender-50601120822")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("breadlicker45/autotrain-blender-50601120822") model = AutoModelForSeq2SeqLM.from_pretrained("breadlicker45/autotrain-blender-50601120822") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 50601120822
- CO2 Emissions (in grams): 0.0201
Validation Metrics
- Loss: 3.568
- Rouge1: 13.876
- Rouge2: 2.094
- RougeL: 10.249
- RougeLsum: 11.729
- Gen Len: 32.892
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/breadlicker45/autotrain-blender-50601120822
- Downloads last month
- 4