Text Classification
Transformers
PyTorch
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use evamaxfield/soft-search with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use evamaxfield/soft-search with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="evamaxfield/soft-search")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("evamaxfield/soft-search") model = AutoModelForSequenceClassification.from_pretrained("evamaxfield/soft-search", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
c4adb70
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Parent(s): f1df9f6
Model save
Browse files- config.json +1 -1
- training_args.bin +1 -1
config.json
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"vocab_size": 30522
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}
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.25.1",
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"vocab_size": 30522
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}
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training_args.bin
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size 3515
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