# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("lightbansal/metadata_postprocess")
model = AutoModelForSeq2SeqLM.from_pretrained("lightbansal/metadata_postprocess")Quick Links
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1277848900
- CO2 Emissions (in grams): 259.9202
Validation Metrics
- Loss: 0.332
- Rouge1: 95.334
- Rouge2: 31.420
- RougeL: 93.922
- RougeLsum: 93.981
- Gen Len: 5.199
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/lightbansal/autotrain-metadata_postprocess-1277848900
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# 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="lightbansal/metadata_postprocess")