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CamemBERT-MedNERF
davanstrien/CamemBERT-MedNERF
CamemBERT-MedNERF is a token classification model from davanstrien. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
- Problem type: Entity Extraction - Model ID: 69856137957 - CO2 Emissions (in grams): 0.1165
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Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 69856137957
- CO2 Emissions (in grams): 0.1165
Validation Metrics
- Loss: 1.510
- Accuracy: 0.706
- Precision: 0.648
- Recall: 0.679
- F1: 0.663
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/davanstrien/autotrain-french-ner-blank-model-69856137957
Or Python API:
from transformers import AutoModelForTokenClassification, AutoTokenizer
model = AutoModelForTokenClassification.from_pretrained("davanstrien/autotrain-french-ner-blank-model-69856137957", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-french-ner-blank-model-69856137957", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Token Classification
- Library
- transformers
- Type
- camembert
- License
- mit
- Languages
- fr
- Created
- Jun 26, 2023
- Updated
- Jun 26, 2023