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autonlp-pos-tag-bosque
Emanuel/autonlp-pos-tag-bosque
autonlp-pos-tag-bosque is a token classification model from Emanuel. Use it when you need labels on individual words, such as names. It is set up for transformers.
- Problem type: Entity Extraction - Model ID: 21124427 - CO2 Emissions (in grams): 6.2107269129101805
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 19, 2021
- SHA
- 145a83cb
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Entity Extraction
- Model ID: 21124427
- CO2 Emissions (in grams): 6.2107269129101805
Validation Metrics
- Loss: 0.09813392907381058
- Accuracy: 0.9714309035997062
- Precision: 0.9721275936822545
- Recall: 0.9735345807918949
- F1: 0.9728305785123967
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/Emanuel/autonlp-pos-tag-bosque-21124427
Or Python API:
from transformers import AutoModelForTokenClassification, AutoTokenizer
model = AutoModelForTokenClassification.from_pretrained("Emanuel/autonlp-pos-tag-bosque")
tokenizer = AutoTokenizer.from_pretrained("Emanuel/autonlp-pos-tag-bosque")
inputs = tokenizer("A noiva casa de branco", return_tensors="pt")
outputs = model(**inputs)
labelids = outputs.logits.squeeze().argmax(axis=-1)
labels = [model.config.id2label[int(x)] for x in labelids]
labels = labels[1:-1]# Filter start and end of sentence symbols
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Languages
- pt
- Created
- Mar 2, 2022
- Updated
- Oct 19, 2021