Downloads · 30 days
7
1% of all-time downloads
autonlp-imdb-sentiment-analysis-623817873
chiragme/autonlp-imdb-sentiment-analysis-623817873
autonlp-imdb-sentiment-analysis-623817873 is a text classification model from chiragme. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 623817873 - CO2 Emissions (in grams): 147.38973865706626
All-time downloads
735
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
- Mar 10, 2022
- Updated
- Mar 10, 2022
- SHA
- ce0eb41c
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 623817873
- CO2 Emissions (in grams): 147.38973865706626
Validation Metrics
- Loss: 0.2412157654762268
- Accuracy: 0.9306
- Precision: 0.9377795851972347
- Recall: 0.9224
- AUC: 0.97000504
- F1: 0.9300262149626941
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 AutoNLP"}' https://api-inference.huggingface.co/models/chiragme/autonlp-imdb-sentiment-analysis-623817873
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("chiragme/autonlp-imdb-sentiment-analysis-623817873", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("chiragme/autonlp-imdb-sentiment-analysis-623817873", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Mar 10, 2022
- Updated
- Mar 10, 2022