demo_knots_1_1 / README.md
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---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "AA sequence with spaces"
datasets:
- dav3794/autotrain-data-demo-knots2
co2_eq_emissions:
emissions: 0.021557396511961088
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Dataset: 1:1 (unknotted : knotted)
- Model ID: 1315550258
- CO2 Emissions (in grams): 0.0216
## Validation Metrics
- Loss: 0.391
- Accuracy: 0.833
- Precision: 0.836
- Recall: 0.823
- AUC: 0.900
- F1: 0.829
## 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/dav3794/autotrain-demo-knots2-1315550258
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("dav3794/autotrain-demo-knots2-1315550258", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("dav3794/autotrain-demo-knots2-1315550258", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
```