Downloads · 30 days
10
3% of all-time downloads
loadedbert1
madmancity/loadedbert1
loadedbert1 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: Binary Classification - Model ID: 49343119213 - CO2 Emissions (in grams): 1.0506
All-time downloads
319
Public
Repo size
2.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.3 GB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 14, 2023
- Updated
- Apr 14, 2023
- SHA
- 66bd7924
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 49343119213
- CO2 Emissions (in grams): 1.0506
Validation Metrics
- Loss: 0.254
- Accuracy: 0.964
- Precision: 0.933
- Recall: 1.000
- AUC: 0.964
- F1: 0.966
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-loadedbert2-49343119213
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("madmancity/autotrain-loadedbert2-49343119213", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("madmancity/autotrain-loadedbert2-49343119213", 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 14, 2023
- Updated
- Apr 14, 2023