Instructions to use clem/autonlp-test3-2101787 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clem/autonlp-test3-2101787 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clem/autonlp-test3-2101787")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clem/autonlp-test3-2101787") model = AutoModelForSequenceClassification.from_pretrained("clem/autonlp-test3-2101787") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"tags" must be an array
Model Trained Using AutoNLP
- Problem type: Binary Classification Urgent/Not Urgent
Validation Metrics
- Loss: 0.08956164121627808
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- AUC: 1.0
- F1: 1.0
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoNLP"}' https://huggingface.co/proxy/api-inference.huggingface.co/models/clem/autonlp-test3-2101787
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("clem/autonlp-test3-2101787", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("clem/autonlp-test3-2101787", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
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