Downloads · 30 days
11
0% of all-time downloads
not_interested_v0
aujer/not_interested_v0
not_interested_v0 is a text classification model from aujer. 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: 1235146886 - CO2 Emissions (in grams): 2.3077
All-time downloads
9.1K
Public
Repo size
2.8 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.4 GB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Aug 9, 2022
- Updated
- Aug 9, 2022
- SHA
- c3b1352e
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1235146886
- CO2 Emissions (in grams): 2.3077
Validation Metrics
- Loss: 0.802
- Accuracy: 0.788
- Macro F1: 0.743
- Micro F1: 0.788
- Weighted F1: 0.782
- Macro Precision: 0.818
- Micro Precision: 0.788
- Weighted Precision: 0.796
- Macro Recall: 0.722
- Micro Recall: 0.788
- Weighted Recall: 0.788
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/aujer/autotrain-not_interested_3-1235146886
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("aujer/autotrain-not_interested_3-1235146886", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("aujer/autotrain-not_interested_3-1235146886", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- en
- Created
- Aug 9, 2022
- Updated
- Aug 9, 2022