Text Classification
PEFT
Safetensors
English
intent-classification
ecommerce
lora
qlora
function-calling
Instructions to use while-ai/ecommerce-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use while-ai/ecommerce-1b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-1b-it-bnb-4bit") model = PeftModel.from_pretrained(base_model, "while-ai/ecommerce-1b") - Notebooks
- Google Colab
- Kaggle
Zero Proof AI commited on
Release verified best 17k checkpoint
Browse filesPublish run 20260716-165442, evaluated on 1,977 held-out conversations with zero train/eval overlap.
- adapter_config.json +4 -4
- adapter_model.safetensors +1 -1
adapter_config.json
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"parent_library": "transformers.models.gemma3.modeling_gemma3",
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"unsloth_fixed": true
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},
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"base_model_name_or_path": "unsloth/gemma-3-1b-it",
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"bias": "none",
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"rank_pattern": {},
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"parent_library": "transformers.models.gemma3.modeling_gemma3",
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"unsloth_fixed": true
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"base_model_name_or_path": "unsloth/gemma-3-1b-it-bnb-4bit",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"rank_pattern": {},
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"revision": null,
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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