Text Classification
PyTorch
Safetensors
sentence-transformers
Spanish
multitask-learning
spanish
intent-classification
Instructions to use PIBotBCCh/pibot-intent-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use PIBotBCCh/pibot-intent-router with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PIBotBCCh/pibot-intent-router") 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
Upload multitask artifacts
Browse files- README.md +1 -1
- encoder/adapter_config.json +2 -2
- encoder/adapter_model.safetensors +1 -1
- encoder/lora_weights/adapter_config.json +2 -2
- encoder/lora_weights/adapter_model.safetensors +1 -1
- heads.pt +1 -1
- train_config.json +2 -2
README.md
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Con este proyecto clonado, también puedes probar:
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```bash
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python -m src.main test --artifact-dir artifacts --text "quiero pagar mi factura" --device cpu
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```
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## Notas
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Con este proyecto clonado, también puedes probar:
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```bash
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python -m src.main test --artifact-dir models/artifacts --text "quiero pagar mi factura" --device cpu
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```
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## Notas
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encoder/adapter_config.json
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"rank_pattern": {},
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"target_modules": [
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"query",
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"value"
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"target_parameters": null,
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"task_type": null,
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encoder/adapter_model.safetensors
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encoder/lora_weights/adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"target_parameters": null,
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"task_type": null,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"query",
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"value"
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],
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"target_parameters": null,
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"task_type": null,
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encoder/lora_weights/adapter_model.safetensors
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size 298128
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heads.pt
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train_config.json
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"model_name": "sentence-transformers/all-MiniLM-L6-v2",
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"max_length": 128,
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"epochs": 20,
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"batch_size":
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"lr_encoder": 2e-05,
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"lr_heads": 0.001,
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"weight_decay": 0.01,
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"task_weight_intent": 1.0,
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"task_weight_context": 1.0,
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"device": "cuda",
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"output_dir": "artifacts",
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"seed": 42,
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"use_lora": true,
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"lora_r": 8,
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"model_name": "sentence-transformers/all-MiniLM-L6-v2",
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"max_length": 128,
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"epochs": 20,
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"batch_size": 10,
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"lr_encoder": 2e-05,
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"lr_heads": 0.001,
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"weight_decay": 0.01,
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"task_weight_intent": 1.0,
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"task_weight_context": 1.0,
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"device": "cuda",
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"output_dir": "models\\artifacts",
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"seed": 42,
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"use_lora": true,
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"lora_r": 8,
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