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smitxxiv
/
Qwen3-Re4B-SQL-TeCoD-TMM

Text Classification
Transformers
Safetensors
English
qwen3
text-to-sql
text2sql
nl2sql
sql
sql-generation
template-matching
template-selection
constrained-decoding
database
nli
paraphrase
reranker
cross-encoder
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use smitxxiv/Qwen3-Re4B-SQL-TeCoD-TMM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use smitxxiv/Qwen3-Re4B-SQL-TeCoD-TMM with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="smitxxiv/Qwen3-Re4B-SQL-TeCoD-TMM")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("smitxxiv/Qwen3-Re4B-SQL-TeCoD-TMM")
    model = AutoModelForSequenceClassification.from_pretrained("smitxxiv/Qwen3-Re4B-SQL-TeCoD-TMM")
  • Notebooks
  • Google Colab
  • Kaggle
Qwen3-Re4B-SQL-TeCoD-TMM
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  • 1 contributor
History: 5 commits
smitxxiv's picture
smitxxiv
Add input format to model card
2a57783 verified 9 days ago
  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • merges.txt
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  • model-00001-of-00002.safetensors
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  • model-00002-of-00002.safetensors
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  • model.safetensors.index.json
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  • special_tokens_map.json
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
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  • vocab.json
    2.78 MB
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