Instructions to use YtBig/tag-h-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YtBig/tag-h-v2 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="YtBig/tag-h-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("YtBig/tag-h-v2") model = AutoModelForSeq2SeqLM.from_pretrained("YtBig/tag-h-v2") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 2346673849
- CO2 Emissions (in grams): 2510.7514
Validation Metrics
- Loss: 1.660
- Rouge1: 52.842
- Rouge2: 28.064
- RougeL: 52.252
- RougeLsum: 52.203
- Gen Len: 11.330
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/Alfred-o/autotrain-tag-h-2346673849
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