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autotrain-chemprot-re-838426740
pier297/autotrain-chemprot-re-838426740
autotrain-chemprot-re-838426740 is a text classification model from pier297. 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: 838426740 - CO2 Emissions (in grams): 0.0911766483095575
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Repo size
2.7 GB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 8, 2022
- Updated
- May 8, 2022
- SHA
- fb09b713
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 838426740
- CO2 Emissions (in grams): 0.0911766483095575
Validation Metrics
- Loss: 0.3866589665412903
- Accuracy: 0.9137332672285573
- Macro F1: 0.6518117007658014
- Micro F1: 0.9137332672285573
- Weighted F1: 0.9110993117549759
- Macro Precision: 0.649358664024301
- Micro Precision: 0.9137332672285573
- Weighted Precision: 0.9091854625539633
- Macro Recall: 0.6551854233645032
- Micro Recall: 0.9137332672285573
- Weighted Recall: 0.9137332672285573
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/pier297/autotrain-chemprot-re-838426740
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("pier297/autotrain-chemprot-re-838426740", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("pier297/autotrain-chemprot-re-838426740", 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
- May 8, 2022
- Updated
- May 8, 2022