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conservative-101-rejection-examiner
MachineLearningLawyer/conservative-101-rejection-examiner
conservative-101-rejection-examiner is a text classification model from MachineLearningLawyer. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 2952885911 - CO2 Emissions (in grams): 1.7615
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Repo size
877 MB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jan 20, 2023
- Updated
- Jan 20, 2023
- SHA
- 2c77af9a
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 2952885911
- CO2 Emissions (in grams): 1.7615
Validation Metrics
- Loss: 0.359
- Accuracy: 0.854
- Precision: 0.744
- Recall: 0.296
- AUC: 0.832
- F1: 0.424
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 AutoTrain"}' https://api-inference.huggingface.co/models/Awesome7749/autotrain-patent-101-2952885911
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Awesome7749/autotrain-patent-101-2952885911", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Awesome7749/autotrain-patent-101-2952885911", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Jan 20, 2023
- Updated
- Jan 20, 2023