Downloads · 30 days
19
4% of all-time downloads
longformer_bbc_news
AyoubChLin/longformer_bbc_news
longformer_bbc_news is a text classification model from AyoubChLin. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
- Problem type: Multi-class Classification - Model ID: 48941118448 - CO2 Emissions (in grams): 1.7385
All-time downloads
457
Public
Parameters
149M
1.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin595 MB · 50%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- longformer
- Access
- Public
- Created
- Apr 12, 2023
- Updated
- Jul 12, 2023
- SHA
- 375564bb
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 48941118448
- CO2 Emissions (in grams): 1.7385
Validation Metrics
- Loss: 0.104
- Accuracy: 0.971
- Macro F1: 0.970
- Micro F1: 0.971
- Weighted F1: 0.971
- Macro Precision: 0.970
- Micro Precision: 0.971
- Weighted Precision: 0.971
- Macro Recall: 0.969
- Micro Recall: 0.971
- Weighted Recall: 0.971
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/AyoubChLin/autotrain-longformer-48941118448
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/autotrain-longformer-48941118448", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/autotrain-longformer-48941118448", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- longformer
- License
- apache-2.0
- Languages
- en
- Created
- Apr 12, 2023
- Updated
- Jul 12, 2023