Text Classification
setfit
Safetensors
sentence-transformers
xlm-roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use mini1013/master_item_top_fd_flat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use mini1013/master_item_top_fd_flat with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("mini1013/master_item_top_fd_flat") - sentence-transformers
How to use mini1013/master_item_top_fd_flat with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mini1013/master_item_top_fd_flat") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -0
config.json
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{
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"architectures": [
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"XLMRobertaModel"
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],
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{
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"_name_or_path": "mini1013/master_item_top_fd_flat",
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"architectures": [
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"XLMRobertaModel"
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],
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