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autonlp-ingredient_sentiment_analysis-19126711
testing/autonlp-ingredient_sentiment_analysis-19126711
autonlp-ingredient_sentiment_analysis-19126711 is a token classification model from testing. Use it when you need labels on individual words, such as names. It is set up for transformers.
- Problem type: Entity Extraction - Model ID: 19126711 - CO2 Emissions (in grams): 1.8458289701133035
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Nov 4, 2021
- SHA
- 0e0b457a
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoNLP
- Problem type: Entity Extraction
- Model ID: 19126711
- CO2 Emissions (in grams): 1.8458289701133035
Validation Metrics
- Loss: 0.054593171924352646
- Accuracy: 0.9790668170284748
- Precision: 0.8029411764705883
- Recall: 0.6026490066225165
- F1: 0.6885245901639344
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/testing/autonlp-ingredient_sentiment_analysis-19126711
Or Python API:
from transformers import AutoModelForTokenClassification, AutoTokenizer
model = AutoModelForTokenClassification.from_pretrained("testing/autonlp-ingredient_sentiment_analysis-19126711", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("testing/autonlp-ingredient_sentiment_analysis-19126711", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Nov 4, 2021