Text Generation
PEFT
Safetensors
English
lora
data-to-text
text-to-data
factual-consistency
hallucination-detection
Instructions to use Loria-MosAIk/xqdt-e2e-qwen3-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Loria-MosAIk/xqdt-e2e-qwen3-4b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B") model = PeftModel.from_pretrained(base_model, "Loria-MosAIk/xqdt-e2e-qwen3-4b") - Notebooks
- Google Colab
- Kaggle
File size: 941 Bytes
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"original_base_model_reference_was_machine_local": true,
"published_base_model_name_or_path": "Qwen/Qwen3-4B",
"schema_version": 1,
"source_checkpoint_relative_path": "checkpoints/checkpoints_e2e19/output_qwen3_4b_e2e19/v1-20260216-031110/checkpoint-8370",
"source_commit": "739c84d868f9d32bcf5c150bdf05c56260cfcaf4",
"source_files": {
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"adapter_model.safetensors": "2fe6abbc06d803b8fd054ec4b5f9dd380cfeb1a88cf729a42b061cd0046f58bb",
"additional_config.json": "c7799462ebedae6557ffad31566029e2d2f958b7b40e46e972cf901bcaf45733",
"args.json": "12178eb164e7a7cb78a31af530ded4ccdb1e08658d877336c3cca752078c4c26",
"reference_predictions": "ee9a6e66da3e220664021ddf34736514e533262c93a87d0d7452cff830c8e6ce"
}
}
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