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--- |
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tags: |
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- autonlp |
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language: en |
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widget: |
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- text: "I love AutoNLP 🤗" |
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datasets: |
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- nihaldsouza1/autonlp-data-yelp-rating-classification |
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co2_eq_emissions: 15.62335109262394 |
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--- |
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# Custom-trained user model |
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- Problem type: Multi-class Classification |
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- Model ID: 545015430 |
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- CO2 Emissions (in grams): 15.62335109262394 |
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## Validation Metrics |
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- Loss: 0.7870086431503296 |
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- Accuracy: 0.6631428571428571 |
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- Macro F1: 0.6613073053700258 |
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- Micro F1: 0.6631428571428571 |
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- Weighted F1: 0.661157273964887 |
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- Macro Precision: 0.6626911151999393 |
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- Micro Precision: 0.6631428571428571 |
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- Weighted Precision: 0.662191421927851 |
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- Macro Recall: 0.6629735627465572 |
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- Micro Recall: 0.6631428571428571 |
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- Weighted Recall: 0.6631428571428571 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ 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/nihaldsouza1/autonlp-yelp-rating-classification-545015430 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("nihaldsouza1/autonlp-yelp-rating-classification-545015430", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("nihaldsouza1/autonlp-yelp-rating-classification-545015430", use_auth_token=True) |
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inputs = tokenizer("I love AutoNLP", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
