Downloads · 30 days
13
3% of all-time downloads
autotrain-screenplay-labeler-78803141065
cledoux42/autotrain-screenplay-labeler-78803141065
autotrain-screenplay-labeler-78803141065 is a text classification model from cledoux42. 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: 78803141065 - CO2 Emissions (in grams): 0.0277
All-time downloads
427
Public
Parameters
334M
2.7 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.3 GB · 50%
Parameter types
How the weights are stored.
F32334M · 100%
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 78803141065
- CO2 Emissions (in grams): 0.0277
Validation Metrics
- Loss: 0.073
- Accuracy: 0.984
- Macro F1: 0.787
- Micro F1: 0.984
- Weighted F1: 0.983
- Macro Precision: 0.783
- Micro Precision: 0.984
- Weighted Precision: 0.981
- Macro Recall: 0.791
- Micro Recall: 0.984
- Weighted Recall: 0.984
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/cledoux42/autotrain-screenplay-labeler-78803141065
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("cledoux42/autotrain-screenplay-labeler-78803141065", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("cledoux42/autotrain-screenplay-labeler-78803141065", 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
- Jul 31, 2023
- Updated
- Jul 31, 2023