Text Classification
Transformers
Safetensors
English
bert
patents
plant-patents
plant-breeding
plant-varieties
paecter
reproducibility
text-embeddings-inference
Instructions to use aydiet/plant-patent-paecter-variety-technology with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aydiet/plant-patent-paecter-variety-technology with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aydiet/plant-patent-paecter-variety-technology")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aydiet/plant-patent-paecter-variety-technology") model = AutoModelForSequenceClassification.from_pretrained("aydiet/plant-patent-paecter-variety-technology", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7fab28e28c00742b497d955bee643ea370a4f32ec4af4732a5ba6a64e06e4c7
- Size of remote file:
- 1.38 GB
- SHA256:
- a0efd4b9877526ed58ede5d2470edbbcd7549d425d951a550f2b0b137b49e7b1
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