Instructions to use Kunologist/navigation-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kunologist/navigation-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Kunologist/navigation-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Kunologist/navigation-chinese") model = AutoModelForTokenClassification.from_pretrained("Kunologist/navigation-chinese") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 2795482484
- CO2 Emissions (in grams): 2.1131
Validation Metrics
- Loss: 0.020
- Accuracy: 0.998
- Precision: 0.984
- Recall: 0.984
- F1: 0.984
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/Kunologist/autotrain-nav-chinese-2795482484
Or Python API:
from transformers import AutoModelForTokenClassification, AutoTokenizer
model = AutoModelForTokenClassification.from_pretrained("Kunologist/autotrain-nav-chinese-2795482484", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Kunologist/autotrain-nav-chinese-2795482484", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
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