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imp_hatred_f
crcb/imp_hatred_f
imp_hatred_f is a text classification model from crcb. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 753423076 - CO2 Emissions (in grams): 0.05286505617263864
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 18, 2022
- Updated
- Apr 18, 2022
- SHA
- 415d7a50
Try a prompt
Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 753423076
- CO2 Emissions (in grams): 0.05286505617263864
Validation Metrics
- Loss: 0.539419412612915
- Accuracy: 0.7616387337057728
- Macro F1: 0.6428050387135232
- Micro F1: 0.761638733705773
- Weighted F1: 0.7592341595725172
- Macro Precision: 0.6606534010647378
- Micro Precision: 0.7616387337057728
- Weighted Precision: 0.7575825822976101
- Macro Recall: 0.6293404928847536
- Micro Recall: 0.7616387337057728
- Weighted Recall: 0.7616387337057728
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/crcb/autotrain-imp_hs-753423076
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-imp_hs-753423076", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-imp_hs-753423076", 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
- Apr 18, 2022
- Updated
- Apr 18, 2022