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bert2
madmancity/bert2
bert2 is a text classification model from madmancity. 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: 45066113192 - CO2 Emissions (in grams): 0.3064
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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
- Mar 30, 2023
- Updated
- Mar 30, 2023
- SHA
- e40fcb44
Try a prompt
Datasets
Model card
From the Hugging Face model README
- Problem type: Multi-class Classification
- Model ID: 45066113192
- CO2 Emissions (in grams): 0.3064
Validation Metrics
- Loss: 0.527
- Accuracy: 0.825
- Macro F1: 0.815
- Micro F1: 0.825
- Weighted F1: 0.816
- Macro Precision: 0.844
- Micro Precision: 0.825
- Weighted Precision: 0.843
- Macro Recall: 0.823
- Micro Recall: 0.825
- Weighted Recall: 0.825
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/madmancity/autotrain-bert1-45066113192
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("madmancity/autotrain-bert1-45066113192", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("madmancity/autotrain-bert1-45066113192", 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
- Mar 30, 2023
- Updated
- Mar 30, 2023