Instructions to use CesarLeblanc/geoplantbert_text_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CesarLeblanc/geoplantbert_text_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CesarLeblanc/geoplantbert_text_classification_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CesarLeblanc/geoplantbert_text_classification_model") model = AutoModelForSequenceClassification.from_pretrained("CesarLeblanc/geoplantbert_text_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9801c5670df4f1580060393449a8e460387224f33f5d4774ca930b8e573a239c
- Size of remote file:
- 1.39 GB
- SHA256:
- 9c7d0048dc65573b7291b2036889f6e18b0345c3c3111fff8eec59693017cdec
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