# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("awacke1/autotrain-livespeechrecognitiontrainingmodelforautotrain-1786761990", device_map="auto")Quick Links
Configuration Parsing Warning:Config file config.json cannot be fetched (too big)
Configuration Parsing Warning:Config file tokenizer_config.json cannot be fetched (too big)
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1786761990
- CO2 Emissions (in grams): 4.1363
Validation Metrics
- Loss: 0.691
- Rouge1: 28.616
- Rouge2: 19.691
- RougeL: 26.461
- RougeLsum: 27.810
- Gen Len: 17.452
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/awacke1/autotrain-livespeechrecognitiontrainingmodelforautotrain-1786761990
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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="awacke1/autotrain-livespeechrecognitiontrainingmodelforautotrain-1786761990")