How to use from the
Use from the
Transformers library
# 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="neil-code/autotrain-test-summarization-84415142559")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("neil-code/autotrain-test-summarization-84415142559")
model = AutoModelForSeq2SeqLM.from_pretrained("neil-code/autotrain-test-summarization-84415142559", device_map="auto")
Quick Links

Model Trained Using AutoTrain

  • Problem type: Summarization
  • Model ID: 84415142559
  • CO2 Emissions (in grams): 3.0879

Validation Metrics

  • Loss: 1.534
  • Rouge1: 33.336
  • Rouge2: 11.361
  • RougeL: 27.779
  • RougeLsum: 29.966
  • Gen Len: 18.773

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/neil-code/autotrain-test-summarization-84415142559
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Dataset used to train neil-code/autotrain-test-summarization-84415142559