Feature Extraction
Transformers
Safetensors
leaf
food
environment
NLP
Eco-Score
products
multilingual
BERT
classification
Open Food Facts
climate
custom_code
Instructions to use baskra/leaf-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baskra/leaf-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="baskra/leaf-large", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("baskra/leaf-large", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 010b80e85ae778360791b54aae8528f7fdfe984bcfca1b962f01b72d9d1b4647
- Size of remote file:
- 2.28 GB
- SHA256:
- 2d8cdc3672fdd3f84cfba73d03edaf865cd2f1741ee4662fdfe5928c38bea281
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