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Upload lora_intent_classifier_roberta-base_model LoRA model

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: roberta-base
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+ tags:
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+ - lora
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+ - semantic-router
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+ - intent-classification
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+ - text-classification
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+ - candle
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+ - rust
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+ language:
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+ - en
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+ pipeline_tag: text-classification
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+ library_name: candle
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+ ---
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+
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+ # lora_intent_classifier_roberta-base_model
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+
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+ ## Model Description
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+
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+ This is a LoRA (Low-Rank Adaptation) fine-tuned model based on **roberta-base** for Intent Classification - Classifies text into categories like business, technology, science, etc..
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+
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+ This model is part of the [semantic-router](https://github.com/vllm-project/semantic-router) project and is optimized for use with the Candle framework in Rust.
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+
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+ ## Model Details
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+
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+ - **Base Model**: roberta-base
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+ - **Task**: Intent Classification
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+ - **Framework**: Candle (Rust)
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+ - **Model Size**: ~476MB
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+ - **LoRA Rank**: N/A
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+ - **LoRA Alpha**: N/A
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+ - **Target Modules**:
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+
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+ ## Usage
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+
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+ ### With semantic-router (Recommended)
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+
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+ ```python
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+ from semantic_router import SemanticRouter
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+
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+ # The model will be automatically downloaded and used
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+ router = SemanticRouter()
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+ results = router.classify_batch(["Your text here"])
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+ ```
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+
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+ ### With Candle (Rust)
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+
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+ ```rust
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+ use candle_core::{Device, Tensor};
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+ use candle_transformers::models::bert::BertModel;
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+
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+ // Load the model using Candle
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+ let device = Device::Cpu;
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+ let model = BertModel::load(&device, &config, &weights)?;
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+ ```
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+
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+ ## Training Details
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+
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+ This model was fine-tuned using LoRA (Low-Rank Adaptation) technique:
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+
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+ - **Rank**: 16
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+ - **Alpha**: 32
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+ - **Dropout**: 0.1
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+ - **Target Modules**:
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+
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+ ## Performance
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+
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+ Intent Classification - Classifies text into categories like business, technology, science, etc.
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+
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+ For detailed performance metrics, see the [training results](https://github.com/vllm-project/semantic-router/blob/main/training-result.md).
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+
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+ ## Files
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+
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+ - `model.safetensors`: LoRA adapter weights
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+ - `config.json`: Model configuration
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+ - `lora_config.json`: LoRA-specific configuration
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+ - `tokenizer.json`: Tokenizer configuration
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+ - `label_mapping.json`: Label mappings for classification
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+
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+ ## Citation
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+
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+ If you use this model, please cite:
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+
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+ ```bibtex
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+ @misc{semantic-router-lora,
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+ title={LoRA Fine-tuned Models for Semantic Router},
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+ author={Semantic Router Team},
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+ year={2025},
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+ url={https://github.com/vllm-project/semantic-router}
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+ }
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+ ```
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+
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+ ## License
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+
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+ Apache 2.0
config.json ADDED
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+ {
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+ "architectures": [
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+ "RobertaForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "dtype": "float32",
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "business",
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+ "1": "law",
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+ "2": "psychology"
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+ },
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+ "initializer_range": 0.02,
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+ "psychology": 2
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+ },
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.56.1",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 50265
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+ }
label_mapping.json ADDED
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+ {
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+ "category_to_idx": {
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+ "law": 1,
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+ "psychology": 2
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+ },
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+ "idx_to_category": {
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+ "0": "business",
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+ "1": "law",
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+ "2": "psychology"
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+ }
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+ }
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tokenizer_config.json ADDED
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