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autotrain-user_needs_full_train_test_split-94165146009
NikoSmow/autotrain-user_needs_full_train_test_split-94165146009
autotrain-user_needs_full_train_test_split-94165146009 is a text classification model from NikoSmow. 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: 94165146009 - CO2 Emissions (in grams): 0.0218
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Oct 10, 2023
- Updated
- Oct 10, 2023
- SHA
- 0d74041a
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 94165146009
- CO2 Emissions (in grams): 0.0218
Validation Metrics
- Loss: 0.471
- Accuracy: 0.869
- Macro F1: 0.388
- Micro F1: 0.869
- Weighted F1: 0.841
- Macro Precision: 0.468
- Micro Precision: 0.869
- Weighted Precision: 0.825
- Macro Recall: 0.358
- Micro Recall: 0.869
- Weighted Recall: 0.869
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/NikoSmow/autotrain-user_needs_full_train_test_split-94165146009
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("NikoSmow/autotrain-user_needs_full_train_test_split-94165146009", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("NikoSmow/autotrain-user_needs_full_train_test_split-94165146009", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- de
- Created
- Oct 10, 2023
- Updated
- Oct 10, 2023