Instructions to use mmcquade11/autonlp-imdb-test-21134442 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mmcquade11/autonlp-imdb-test-21134442 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mmcquade11/autonlp-imdb-test-21134442")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mmcquade11/autonlp-imdb-test-21134442") model = AutoModelForSequenceClassification.from_pretrained("mmcquade11/autonlp-imdb-test-21134442", device_map="auto") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"tags" must be an array
Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 21134442
- CO2 Emissions (in grams): 298.7849611952843
Validation Metrics
- Loss: 0.21618066728115082
- Accuracy: 0.9393
- Precision: 0.9360730593607306
- Recall: 0.943
- AUC: 0.98362804
- F1: 0.9395237620803029
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://api-inference.huggingface.co/models/mmcquade11/autonlp-imdb-test-21134442
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("mmcquade11/autonlp-imdb-test-21134442", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("mmcquade11/autonlp-imdb-test-21134442", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
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