Text Classification
Transformers
Safetensors
modernbert
routing
llm-routing
prompt-classification
multilingual
text-embeddings-inference
Instructions to use scombat/s1d1-router-6src-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scombat/s1d1-router-6src-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scombat/s1d1-router-6src-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scombat/s1d1-router-6src-tiny") model = AutoModelForSequenceClassification.from_pretrained("scombat/s1d1-router-6src-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
variant.json: sigma, max_length, score_center, score_scale
Browse files- variant.json +8 -2
variant.json
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"backend": "torch",
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"recipe": "torch fp16",
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"source": "trained in this project (pipeline/05_train.py, pipeline/07_variants.py)",
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"parameters": 24047637
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"backend": "torch",
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"recipe": "torch fp16",
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"source": "trained in this project (pipeline/05_train.py, pipeline/07_variants.py)",
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"parameters": 24047637,
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"sigma": 0.1229,
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"sigma_rows": 4850,
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"sigma_date": "2026-10-20",
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"max_length": 1024,
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"score_center": 0.5,
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"score_scale": 0.25
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}
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